Are data centres bad? Should Ontarians prevent them from being built here?

The question is pressing. In Mississauga, Prologis has filed the city’s first application for a hyperscale data centre; if you click through that link, you’ll find the headline of the newspaper report opens with “Shut It Down”. On 29 July, the week following original publication of this issue of Changing Lanes, City Council will vote on whether to impose a one-year pause on new data-centre applications, with at least half of councillors reportedly onside. In Hamilton, a proposal for the former Stelco lands moved City Council there to consider a moratorium on new data centres. That would have been a first for a Canadian city, had it passed. It did not, with Council voting it down on 15 July, 10 to 6. That same week, just to Ontario’s south, New York became the first American state to freeze new hyperscale permits altogether. Everyone is deciding at once, but there’s no emerging consensus.

At least some of my friends and family have already made up their minds. They’ve decided that data centres are bad neighbours. They take in too much water, using up some and polluting the rest. They jack up electricity bills (what Ontarians call hydro), while employing almost nobody. Some people I like and some I love sincerely hold this view, as do many people I don’t know. When Abacus Data, the polling firm, asked Canadians whether they would welcome a data centre in their own community, only 16 per cent said yes.¹

I’ve read my Andy Masley (constant readers of Changing Lanes will remember his framework from “Robotaxis Are the New Data Centres”), so I had my priors that data centres were a mitigated good. Still, this is happening where I live, and people I respect have opposite intuitions. So I have set out to answer the question: who is right? What should a reasonable person in Ontario, watching the AI build-out arrive on the Lake Ontario shoreline, want to happen?

Normally in my Changing Lanes pieces I give the verdict up front, but this time I’m going to resist. I want to take the objections seriously and follow the evidence where I think it leads. I hope that by following along, you’ll see the conclusion is reached honestly, and therefore take it seriously.

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Begin with a definition of what we’re talking about. A data centre is a warehouse of computers; indeed, it’s reasonable to think of it as a giant computer, just like a desktop machine, but at the scale of a building rather than a tower case. It has rack upon rack of servers. These store data and run computations, providing support to everything that happens ‘in the cloud’. Historically that has meant providing the engine that runs Internet powerhouses like Gmail or Microsoft Office 365, but also any humble firm offering a mobile app that uses remote data. By some counts there are as many as 108 data centres operating along Lake Ontario. Things are changing, though: the AI boom needs vast amounts of the ‘compute’ that data centres provide, meaning that they are a bigger business than ever. Accordingly, Microsoft is expanding its footprint in Vaughan and across the GTA, and more centres from more firms will follow.

High Performance Computing Center Stuttgart HLRS 2015 07 Cray XC40 Hazel Hen IO.jpg by Julian Herzog is licensed under CC BY 4.0.

Once built, a data centre needs two things. It needs abundant electricity, ideally sustainably generated, because the servers are always on. And it needs cooling, because nearly every watt of electricity that enters a chip leaves it as heat, and if that heat is not removed promptly, the chips fail. Cooling can be accomplished with electricity—think the fans installed inside your desktop machine—but at the data-centre scale, it’s also done with water. Ontario is unusually fortunate in these regards, with Great Lakes water, cold winters, and one of the cleanest power grids on the continent. That’s why data-centre operators are keen to build them here.

Let’s see if we should let them.

Water Fears Are Overblown…

Let’s start with water. There are two claims here: that data centres will poison the water, and that they will use it up.

Poisoning the water, or (to put it more precisely and less emotionally) contaminating it, essentially does not happen during normal operation. Some data centres cool themselves with closed-loop systems, meaning cold water is run through pipes in the building, absorbing heat, which is later released outside. The circulating water sits in a sealed loop and is reused continuously, topped up only to make good small losses. It only touches pipework, and never the servers nor the outside air. This delicate use of water is in sharp contrast to other Ontario industrial sectors, like paper or metal. Unlike a pulp mill, there is no process effluent to speak of. Unlike a mine or ore refinery, there is no tailings pond.2

Using up the water, or (to put it more precisely and less emotionally) consuming it, is a stronger charge. Many data centres, rather than using closed-loop systems, cool evaporatively. In these cases, the servers heat the air around them, and this heated air is channelled over water. That water evaporates, taking the heat with it.

Whether this is a problem depends on where that water came from. If it’s drawn from an aquifer, on any human timeframe that water is lost forever. If it’s drawn from a river, it might permanently exit the watershed; if the water is taken from the river far enough upstream, that water will never reach the downstream system. If that is practiced at scale in suboptimal places, the water loss is real, and enormous. In Mesa, Arizona, for example, a single campus holds standing permission to ramp from one million to four million gallons a day, half of it drawn from the Colorado River. That is a genuine loss, because the Colorado is a closed, badly over-allocated basin. Water evaporated off a cooling tower there leaves as vapour that rains out far downwind, never returning to the watershed in any usable quantity.

But southern Ontario lies almost entirely within the Great Lakes–St. Lawrence basin. Here, evaporative draw offers a negligible chance of watershed loss; water taken from the watershed evaporates into the air and returns, via the water cycle, to that watershed. So nothing is consumed.

Well, almost nothing. The international compact governing the lakes will formally count evaporative cooling as a loss, since some negligible vapour rains out beyond the basin. But the quantities at stake are minute against the scale of the lakes, which hold roughly a fifth of the world’s surface fresh water. No array of evaporative-cooling data centres we can realistically contemplate would amount to more than a rounding error.

That is stipulating that such an array would be constructed. That’s unlikely. Evaporative cooling is a design choice, and architects choose it for data centres to be built where the air is hot and dry. Ontario has many virtues, but a hot and dry climate is not one of them. Across autumn, winter, and spring, southern Ontario’s daily mean temperature sits well below the mark (roughly 18°C) at which outside air alone can cool a data centre. In particular, Toronto’s seasonal means run from about −2°C in winter to 8°C in spring. This means that the province can cool without water through something like three-quarters of the year. In warmer months, the lakes remain cold, and data centres take advantage. Equinix, the world’s largest data-centre operator, cools its downtown Toronto facility from Enwave’s deep-lake loop, which pulls near-freezing water off the bottom of Lake Ontario. Meanwhile, Microsoft says its Ontario sites draw municipal water for cooling only when temperatures exceed about 29°C. That happens for less than five per cent of the year.

There are many horror stories about data-centre water consumption, but they all happen in arid regions. Even there, the stories lack any sense of proportion. Maricopa County, Arizona, one of the biggest data-centre markets on the continent, expected its data centres to use about a billion gallons of water in 2025. That seems bad… until one learns that the county’s golf courses were expected to use twenty-nine billion. By the same token, if Ontario is concerned about wasting water, rather than get concerned about what data centres may do, we should look instead to the ways we use water now. Concern on that front is conspicuous by its absence.

Is there anything critical to say about water and data centres in an Ontario context? Only that our systems need good data to make good decisions. There was a mild flap when it was found that one Quebec facility had no water meter at all. We can’t audit what we don’t measure, so even though Ontario’s climate makes heavy water use unnecessary, let’s meter every facility, including those buying city water, which today’s permit rules don’t reach. Let’s publish the readings, tracking against a cap on use, which we should write into the servicing agreement. Developers have historically fought disclosure, but I would expect that they won’t fight hard in an Ontario context, because they know just how little water they will use.

…Electrical Fears Are Not

In contrast to concerns about water, concerns about hydro (which, confusingly, is how Ontarians refer to commercial electricity) are real. Data centre electrical loads can be staggering. A single centre, if large enough, can draw as much power as a mid-sized city. The hyperscale campuses now being contemplated are designed for anywhere from 300 megawatts to a full gigawatt of continuous load. For context, a gigawatt is roughly the output of one of Darlington's nuclear reactors, or enough to power some 800,000 homes.

Demand on this scale is not hypothetical. As of this month, data-centre projects totalling some 7,000 megawatts have active requests to connect to Ontario’s grid. Ontario’s electric operator, the IESO, now expects data centres to make up 8.6 per cent of Ontario demand in 2050, more than half again what it forecast a year ago.

Adding this much demand to a neighbourhood can create two problems for everyone else: it can raise the price of electricity, and it can require the addition of expensive new infrastructure. In the abstract, this might be a problem; but in Ontario, there are rules in place that mean the power costs of a data centre aren’t socialized.

Let’s start with prices. The data centre pays for what it uses, just like any other large industrial customer. Believe it or not, that can be good. A quirk of Ontario’s system, thanks to its nuclear plants delivering high baseload power, has meant that during some nights Ontario has surplus power it has had to sell at a loss. Always-on data centres can soak up that capacity, meaning the system’s fixed costs get spread across more electricity sales. But of course, during some peak periods, Ontario does not have enough power. In those hours the marginal generator is a natural-gas plant, meaning that a data centre running flat out through a July heat wave is (at one remove) burning natural gas. More gas hours mean more emissions and higher market prices, and both land on everyone.

The fix is giving us the right to interrupt the flow to big data centres if we need to. Texas and Alberta already do this, connecting them faster in exchange for curtailment during the tightest hours of the year. A data centre that we can throttle back for the fifty worst hours costs the system little; if they don’t want to be throttled, they should simply be required to pay for the peaker they make us run.

Ontario seems to be on its way to this requirement already. Bill 40, passed in December, lets the province decide which very large loads serve its economic interests and may connect to the grid, and the IESO published draft technical requirements for large computational loads in May. The pieces of a sensible large-load regime are on the table; the one that is missing is the public’s ability to throttle data centres’ electrical use if necessary.

Of course, the centres may very well choose to throttle themselves. Ontario’s power system has a bizarre feature where it computes everyone’s share of the system’s fixed costs (the ‘global adjustment’) by tracking their usage during the five heaviest hours of the year. There is a whole system of consultants that advise clients on how to anticipate those hours, throttle back use during them, and thus shift their costs onto someone else. (How do I know this? Don’t ask.) Data centres, with batteries and flexible workloads, would be excellent players of that game. That, more than anything, is why Ontario should refine the global-adjustment system, and more than that, designate a new rate class for very large consumers, to discourage this kind of game-playing.

On the question of infrastructure, there is good news: in Ontario, a data centre that requires extension of the local grid cannot just hand that bill to the public. The utility estimates what the new wires, transformers and substations will cost, compares that with the revenue it expects to collect from the customer, and can require the developer to pay the shortfall. It can also demand a deposit, retaining it if the promised demand never appears.

So if a new substation exists only to connect the data centre, the centre will largely pay for it. The weaker point is farther upstream. If the project requires reinforcement of the shared transmission network, that work may be rolled into the regulated cost of the provincial grid. Sometimes that is reasonable: a larger line may benefit an entire growing region. But if a billion-dollar upgrade is needed principally for one enormous customer, spreading the cost across everyone’s hydro bills would amount to a public subsidy.

So what we see is that there are reasonable concerns to be had about data centres and electricity. A new data centre will not automatically raise its neighbours’ bills, and Ontario protects ratepayers from much of the cost of connecting it. The danger is that enough centres might spike the cost of dirty peaking power in the near term, and in the longer term might require big investments in new generation and transmission infrastructure.

In my view, those are investments that Ontario should be making anyway. We should be building clean generation, at scale, now; and we should be doing that irrespective of how many data centres are knocking at the door.

As has pointed out, Ontario is one of the few jurisdictions in the world right now that knows how to build nuclear on time and on budget. We should be building more of it while our expertise is current (a case that Eric Lombardi made in these pages last month). At the same time, we should be supplementing with wind and solar, which are cheap and fast to add (thanks, China!). Building more capacity now is sensible; even if no data centre ever came to Ontario, electric vehicles have already arrived, and more are coming. The province’s ambitions in battery manufacturing, rare-earth processing, and other 21^st-century industry will all rest on cheap, green power. Let’s build for that, and let data centres come along for the ride.

Other Concerns Are Modest

Beyond water and electricity, the remaining objections to data centres are mild and resolvable.

Large data centres hum. They emit a continuous, low-frequency drone from thousands of cooling fans, joined intermittently by the roar of backup generators on their test runs. The hum is a by-product of active cooling, so a small or fully liquid-cooled facility can be nearly silent; the sites that draw complaints are the big, air-cooled ones. These emissions can be measured; monitors at homes near American facilities have recorded outputs of 40 to 59 decibels. In the abstract, that range runs from ‘quiet library’ to ‘a window air conditioner’. Residents near facilities in Virginia have described it as ‘a jet engine that never turns off,’ with some sealing their windows or sleeping in earplugs. Those accounts warrant some amount of skepticism, since neighbours fighting a project have every reason to dramatize, but we shouldn’t dismiss them.

Here Ontario holds a lever most American jurisdictions lack. NPC-300, the province’s environmental noise guideline, does two useful things: it sets numeric limits at the property line (40 decibels at night in rural areas), and it requires a noise study before approval. In much of the United States, neighbours discover the hum first and go looking for a remedy second, but in Ontario, the remedy can be written into the permit before construction.

It’s true that NPC-300’s limits are tuned more-or-less to the midrange frequencies that human hearing notices most (the technical term is A-weighted). That standard can undercount low-frequency tonal drone, which is harder to notice consciously but can be subconsciously unsettling. Fortunately, Ontario’s noise rules already penalize tonal sound, adding five decibels to the measured level of a steady hum. The real gap is procedural: smaller facilities can self-register without a full study. For a hyperscale site, the province should insist on the full noise assessment for each one.

Another complaint we often hear is that for all their costs, data centres contribute nothing to the communities that host them. That’s true, I suppose, if we count contributions as jobs. A large campus needs few people, on the order of 20 to 30 permanent staff per 100 megawatts of capacity. While it takes thousands of jobs to construct them, maintaining them doesn’t require very many people.

But if we count contributions as property tax, it’s a different story. Exhibit A here is Loudoun County, Virginia, the densest data-centre cluster on earth, where the industry supplies 38 per cent of the county’s general fund from four per cent of its commercial land. Sadly that example is not applicable to Ontario. Loudoun taxes the servers themselves, reassessed as the equipment refreshes. Loudoun levies a business tangible personal property tax on the computer equipment itself, and a hyperscale building refreshes tens of thousands of servers on a rolling cycle, each round taxable. Ontario municipalities don’t do this. Instead they tax the land and the building, and the building is, for assessment purposes, a warehouse. Still, while no fountain of cash like in Virginia, data centres do employ people and pay taxes, meaning a city is better off having them than not.

So a data centre is a quiet, low-traffic, low-employment industrial site. That’s faint praise, but it has an upside, which is that the small scope of gain means that Ontario communities have standing to bargain hard on what they get out of permitting them.

What a Reasonable Ontarian Should Want

But if the gains are so modest, why permit them at all?

Part of it is that refusing permission doesn’t mean they’re not built, it just means they’re built elsewhere. Projects turned away in the United States have flowed toward Texas and Arizona: thirstier places, on dirtier grids. So the blocking places remain free of them, at a net cost to the environment. Similar dynamics are playing out in Canada: Quebec, rich in water and clean power, has capped new data-centre power as a matter of policy, and British Columbia has done much the same. Alberta, with the dirtiest grid of the three and constant stress on its water supply, is where the overwhelming majority of Canada’s proposed capacity has piled up, some of it as off-grid gas megaprojects. Refusal in a clean-grid province is, in practice, an invitation to a dirty-grid one.

Another part, strange to report, is the company that refusal keeps. The New York Times reported this month that state-linked accounts from China, Russia, and Iran have been flooding social media with AI-generated slop warning that data centres will drain the water and wreck the grid. American officials read the campaign as an effort to fan public opposition and slow the West’s AI build-out. That does not make my worried friends and neighbours into foreign dupes, since the West’s enemies are inflaming sincere grievances rather than inventing them, and it is those sincere grievances I’m trying to address here. But when our adversaries spend covert effort discouraging us from building something, they are telling us that they think it’s valuable.3

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In my view, Ontario should host as many data centres as its clean supply can carry, because the objections are weak. Water is immaterial, noise can be regulated easily, and power capacity is something we should be building anyway.

What should a reasonable Ontarian seek in return for permitting data centres to be built here? Three things:

1. Meter the water, publish the readings, and cap the draw in the permit.

2. Require a full, tonal-aware noise study and provincial approval, including penalties for exceeding noise limits, in advance.

3. Make developers pay for their own connections, including a fair share of upstream transmission, give very large loads their own rate class, and connect the biggest loads on interruptible terms.

Meanwhile, Ontario should be building clean power generation: renewables immediately, the nuclear Ontario has shown it can deliver, and the transmission lines to carry it where we need it. Those are unambiguous goods even if no data centre ever connects to them.

The citizen’s answer to a data centre shouldn’t be no. It should be yes, with conditions.

On 16 July I'm joining the Parking Reform Network to discuss what cities should want from automated vehicles. On 21 July I'll be at the 2026 Toronto Robotics Conference, on a panel asking whether robotaxis really are safer than humans. And on 23 July I will host Aurora's Chief Safety Officer, Nat Beuse, on the next Changing Lanes Live, for a discussion of freight automation and safety.

I hope to see readers at all of these events! Please follow the links to register.

How safe is safe enough? If we’re going to regulate driving automation, we must have an answer to this question.

Let’s put it simply. Choose a metric for road safety: candidates might be ‘collisions with another vehicle’, ‘collisions with a pedestrian or cyclist’, ‘collision with anything at all’, ‘incident causing death’, ‘incident causing serious injury’, or ‘incident of any sort that required a police report’. For a given period, an automated-driving system (ADS) will be involved with a certain number of such collisions or incidents.

The question is: what is the target number, such that, if an ADS falls below that target, we can consider it safe to deploy; and if it falls above, we do not?

A lot is at stake. If we pick a target that’s too high, the ADS will cause incidents that wouldn’t have happened otherwise. But if we pick one that’s too low, human drivers will cause incidents that an ADS would have avoided.

In June 2026, Families for Safe Streets (FSS) offered their own answer to the question. FSS is a national advocacy organization founded in 2014 by people whose loved ones were killed or seriously injured in traffic incidents. FSS’s answer was released as Safety First, Always: An FSS Framework for Autonomous Vehicles. At its centre sits a proposed certification standard the paper calls the Gain and Guard Rule: before full-scale commercial deployment, automated vehicles must be at least ten times safer than human drivers on average across everywhere they operate, and never worse than human drivers in any single operating environment.

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In the spirit of disclosure: I contributed time and expertise to this framework as an outside contributor. Consequently, my name appears in the acknowledgements, and the FSS website hosts my explicit endorsement. As you read the following, please be aware that this is a review of work that I had a hand in, and that I want to succeed. Against this, the framework itself notes that acknowledgement as a contributor “recognizes contribution, but not necessarily endorsement of every statement or position”.

In that spirit, I will reveal my cards. I regard Safety First, Always as a serious effort to give regulators a public, measurable standard, and the Gain and Guard Rule is the kind of bar we need.

Having said that, I have two reservations.

Firstly, the framework’s moral core, the Guard prong, has a measurement problem the framework doesn’t solve… but fortunately, in my view the framework already contains the seed of a solution. Secondly, its liability proposal correctly borrows from the aviation sector, but doesn’t borrow enough.

Neither concern displaces my enthusiasm for what FSS has done here. I offer both reservations, and the first one especially, to help make the framework’s strongest idea enforceable.

A High Bar, but Not Too High

The rule’s plain-language version is that wherever it operates, an ADS must be at least ten times safer than human drivers on average wherever it operates (i.e., its operational design domains), and never worse than human drivers in any single area.

An operational design domain (ODD) is the set of conditions a system was built and is authorized to handle. It can consist of a defined geography, certain road types, certain weather, or certain hours. The easiest possible ODD might be “on a pre-mapped highway, during the day, with no clouds”. The hardest one would be “everywhere”.¹

The Gain prong demands a tenfold reduction in fatality, injury, and crash rates (as an exposure-weighted average) across all a system’s authorized ODDs. The Guard prong forbids performance within any single ODD that is worse than human driving.

The point of the Gain prong is to demand order-of-magnitude improvement overall, while the point of the Guard prong is to prevent ‘gaming’ of that demand. In the latter’s absence, an unscrupulous firm might point to their strong performance on average while concealing dangerous performance in particular conditions, or neighbourhoods.

To see why this matters, consider the benchmark it replaces.

The dominant standard in automated vehicle (AV) governance, embedded in UNECE working documents and Britain’s Automated Vehicles Act 2024, and echoed in the academic and industry benchmark models cited in American AV safety cases, is that an ADS should drive as safely as a “competent and careful” human. That sounds reasonable until you remember what human driving produces: in 2023, that was more than 40,000 deaths and roughly 2.4 million injuries on American roads. As Prof. Bryant Walker Smith, my guest on a recent episode of Changing Lanes Live, puts it: I am concerned about automated driving, but I’m terrified of human driving.

The first question to ask about this is whether asking for 10x improvement over a human standard is reasonable. Perhaps that’s expecting too much? To judge by the performance of the industry leader, it is by no means expecting too much: at time of writing, Waymo’s safety data hub reports, across more than 220 million driverless miles, 94% fewer serious-injury crashes and 82% fewer injury-causing crashes than human benchmarks in the same cities. A peer-reviewed study with the reinsurer Swiss Re found comparable reductions in bodily-injury liability claims. And Waymo is performing so well in conditions that, far from being cherry-picked, are among the most difficult: dense, high-interaction city streets, full of pedestrians, cyclists, and unpredictable human drivers.

It’s worth reflecting on the fact that Swiss Re was Waymo’s partner in this exercise. It’s a reinsurer, a firm whose whole business is pricing risk with its own capital. As such, it has ‘skin in the game’ when it assesses those safety numbers. Put more formally, its assent is a costly signal that the claims are trustworthy. That’s why I’m more sanguine about these figures than other researchers, or Safety First, Always seems to be, with its calls for independent verification. Let’s set the disagreement aside, and stipulate for now that Waymo’s safety record is true.

If so, it means that FSS has set its floor at a level that at least one company in the sector has already reached. If Waymo’s numbers are real, the Gain prong costs Waymo nothing except the freedom to backslide, and it requires Waymo’s competitors to clear the same bar. If they can’t, that means the standard is working as intended. When FSS asked me to comment on the framework, this is one point that I made: regulators will know they have the right bar if they can offer one which some systems clear, but others can’t.

The strongest objection to the ten-fold threshold is that it asks too much. An academic framing of this claim comes from RAND; in 2017, researchers at that firm modelled deployment policies and found that waiting for nearly perfect AVs costs lives. Putting vehicles on the road when they are merely somewhat better than humans saves more people over thirty years than holding out for 75% or 90% improvements. This is a formal phrasing of the plain-language argument I often hear from intelligent laypeople: once driving automation is even a hair better on average than a human driver, the smart play is to move immediately to full deployment, because otherwise you are losing lives on net.

Safety First, Always has an answer to this, which is a staged certification pathway. As per this proposal, systems that don’t yet reach the 10x level may still operate in public, but must do so through supervised stages, with example thresholds of 2X and 4X as permissible for pilot projects. The full Gain requirement is reserved for full-scale commercial deployment. There are still opportunities for lives to be saved on net, just in bounded circumstances, and AV firms are still able to practice in real environments, to improve and gain the opportunity to reach the 10X level.

This is also Safety First, Always’s reply to the worry that a floor that only the incumbent clears is a moat, using early gains in safety to lock in a de facto monopoly. The 10x floor governs full commercial scale, while the supervised 2X and 4X stages keep a path open for challengers, and competition.

The Guard Prong’s Problem

The Guard prong is the framework’s moral core. It exists so that a company cannot buy a glowing citywide average with excellent freeway performance, while at the same time offering something worse than the status quo to some subset: a particular district, or time of day, or group of people (say, people in wheelchairs). That concern is valid, and I have written, on several occasions, about it; this behaviour is one that even Waymo has seemed to engage in.

Safety First, Always seeks to solve the problem, while adding a requirement I haven’t seen stated so directly elsewhere: demonstrated detection parity across skin tones, ages, body types, and mobility devices, treated as a condition of certification rather than an aspiration, and grounded in documented disparities in pedestrian-detection research.

I acknowledge that this is an important bar we must insist be cleared. That’s why I am surprised that, in this context, the framework does not make the obvious move of saying that AVs must, as I once argued in Asterisk, use multiple sensor types rather than cameras only. That idea is gestured at here, but only as a fail-safe design principle (to prevent one sensor malfunctioning from leaving the vehicle ‘blind’) rather than a way to ensure all vulnerable road users are protected. I would have placed the multi-sensor rule in the vulnerable-road-user argument, and not merely the redundancy one.

Quibbles aside, my concern is that the Guard prong is easier to state than to implement.

That’s because fatal crashes are rare events. Yes, 40,000 Americans die on the roads (on average) each year, but that number must be put in the context of just how much Americans drive: American roads produce roughly one death per hundred million vehicle-miles. This means that, to be confident that an ADS is safer than average requires it to have been tested for many hundreds of millions of miles, into the billions.

The Gain prong survives this because it aggregates; it takes exposure-weighted averages across all ODDs, measured on the more frequent currencies of injuries and crashes as well as deaths. Waymo’s record to date excels on this requirement. The Guard prong, by design, disaggregates, looking into smaller and finer individual operating domains. Waymo’s record is no answer here. As an aggregate, exposure-weighted claim on the frequent currencies of injuries and crashes, the data does not offer a per-ODD fatality claim.

The problem, as I see it is that the smaller the dataset, the more chance plays into the matter: given a small enough set, one cannot confidently distinguish a genuinely worse-than-human ADS from one that was merely unlucky. That means that the Guard rule could take us into a bad equilibrium, where one incident in a small domain disqualifies the entire ADS everywhere. The equal-but-opposite failure would be to dismiss any such incident in a narrow ODD as noise rather than signal. Preventing these bad equilibria depends on defining the ODDs just right. The framework calls for regulators to shoulder this responsibility, and I don’t envy them the job.

Fortunately, the task need not be improvised fifty times over. Defining ODDs is exactly the kind of scarce technical work the framework’s own proposed interstate compacts exist to pool: the first product of such a compact should be a shared, pre-registered ODD taxonomy, with agreed minimum sample sizes before any single domain’s record is treated as signal rather than noise. Standardize the denominator once, centrally, and the Guard prong stops depending on each jurisdiction guessing right on its own.

Conversely, the regulator tasked with implementing Safety First, Always is gifted with a strong enforcement framework, the ‘Lawful AV’: a tiered system of regulatory triggers, review, then suspension, then revocation, for persistent unlawful behaviour, even when no crash results (think passing stopped school buses or blocking crosswalks). Safety First, Always takes the view that safety should not just be measured in death or injuries, but in behaviours that tend to promote these things. That’s table stakes in aviation: airlines can face mandatory reporting, review, and suspension or revocation of license to operate for regulatory violations, even those where there’s no incident. The framework argues that AVs should be regulated the same way.

I’m all for this, because this rule is empirical: it counts observable events against defined thresholds, rather than estimating rare-event rates. I think that this is the repair the Guard prong needs. As written, the Guard prong asks whether an ADS is worse than a human at causing death within a single ODD, which our data is insufficiently detailed to answer. Worse, the question gets harder as AVs get better: the safer the vehicles, the rarer the fatalities, and the larger the sample you would need to prove anything at all. The way out is to put the Guard prong on the same footing as the Lawful AV rule, i.e., to judge each domain on the metrics of injuries, crashes, insurance claims, and unlawful-but-harmless behaviours.

One might object that the Guard prong is left un-operational on purpose. FSS is a coalition of the bereaved, and no one can expect it to offer a document that translates ‘never worse’ into an acceptable per-neighbourhood death rate. If that is their view, I am entirely sympathetic. But a regulator is entitled to reply that a target no one can measure is a target that protects no one. Giving the prong something it can count is what will give the moral argument teeth.

If We’re Going to Copy the Aviation Sector, Let’s Go All the Way

Safety First, Always also looks to aviation regulation to help solve the most vexed problem in the AV space, namely liability.

FSS members know all too well that today’s road-incident victims routinely spend years in fault litigation before receiving compensation. That’s bad enough, but the advent of vehicle automation is poised to make it worse by multiplying the defendants, from manufacturer only to a host of suppliers (sensors and mapping most obviously, but also fleet operators, chips, wireless Internet, and on and on.) The paper’s answer is a two-tier structure with an honourable lineage running through the Montreal Convention and Wansley’s The End of Accidents: automatic strict liability up to a defined threshold, no proof of fault required, with presumed but rebuttable company liability above it.

This is the right position, one that I have advocated for myself. As Safety First, Always puts it, people harmed by AVs should not face higher barriers to compensation than airline passengers, where liability is predictable and capped. This approach is preferable to endless litigation, which is bad for victims, and to ‘jury roulette’, which is bad for firms. There is even a plausible legislative bargain to get there (though the framework doesn’t spell it out): strict AV firm liability, traded against some form of certainty on damages that can be claimed.

FSS proposes a pooled industry-compensation fund, financed by the full range of AV companies that would pay victims immediately while the companies sort out cost allocation afterward. While Safety First, Always argues this is aviation-inspired, I think they are mischaracterizing it: in that sector, liability is carrier-by-carrier, backed by mandatory insurance, rather than mutualized across the industry. There’s good reason for this: unless contributions are sharply risk-rated, the safest operator ends up subsidizing the crashes of the worst one. In the AV industry today, there is quite a spread between the most- and least-safe operators (I’ll forbear from naming names); a market-share-financed pool is an invitation to moral hazard.2^[2] As such, the proposal sets itself up to receive the stiffest opposition from the safest operators, which would be a perverse outcome.

Although it doesn’t say it, I suppose that the framework is drawing upon a different industry when thinking about risk, namely nuclear. The Price-Anderson Act has run the American nuclear industry on this model for seventy years: a mandatory, industry-wide pool that pays victims first and allocates fault later. That regime was put in place because no single operator could carry the tail risks of a high-consequence, immature technology alone. Unfortunately, nuclear operators are judged against a risk-rated formula, into a small, homogeneous, heavily-inspected industry. The AV field is none of those things.

There is also the question of feasibility, and of venue. A statutory compensation fund requires legislation, and the paper concedes liability rules “may ultimately need to be federally established,” which is awkward at a time that, as I pointed out in Reason, Congress is failing to agree on AV oversight, and the regulator is withdrawing voluntary safety oversight programs. The nearer-term market is the states, which are already writing AV law. To its credit, the framework knows it: everything in it is framed as a floor adoptable at any level, with interstate compacts proposed to pool scarce technical capacity.

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How safe is safe enough? Safety First, Always offers an answer: ten times safer everywhere you operate, never worse anywhere. That is a concrete standard, one with real moral weight, as it’s offered by the people who have already suffered from the frailty of human driving. The real test of the framework is whether a single jurisdiction adopts it whole: Gain, Guard, and Lawful AV together. In that regard, I note that Transport Canada issues non-binding safety guidance and sets vehicle standards, while provinces control who may operate on their roads. Ontario might adopt the Gain and Guard Rule and the Lawful AV framework without waiting for Ottawa, and I would like to see it do so.

Respect to for comments on an earlier draft, and to the FSS team for letting me review the framework before publication.

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Autonomous Vehicles & Parking Reform

Thursday, 16 July, 1500h ET

One week from today (at time of writing), I’m joining a panel hosted by the Parking Reform Network (PRN) to ask what urbanists should want out of automated vehicles, and how to move from ‘hope’ to ‘a plan’.

Hosted by the PRN’s Tony Jordan, I’ll join Dr. Miriam Pinski of UCLA’s Shared-Use Mobility Center and Dr. Rachel Weinberger of the Regional Plan Association. The three of us are united in our hopes for better cities, but may be divided in our views on how to get there. Expect a spirited conversation that talks through the policies that would let cities benefit from an AV future, and the consequences if we do nothing.

It’s an online webinar on Zoom, and free to attend. Please register here.

Changing Lanes Live, with Nat Beuse, CSO of Aurora

Thursday, 23 July, 1200h ET

The following week, my guest on the third episode of Changing Lanes Live will be Nat Beuse, Chief Safety Officer of Aurora, the world’s leading driverless-trucking company.

Nat Beuse, image courtesy of Aurora

Few people have seen automated-vehicle safety from as many angles. Beuse spent nearly two decades at NHTSA, where he oversaw the US government’s work on automated driving, then led the safety team at Uber’s self-driving unit, before joining Aurora. We’ll talk about the challenges that face self-driving heavy haulers; the extent to which Aurora’s problems resembles those of robotaxi companies, and the unique challenges the firm faces; the foundation of the firm’s sterling safety record; and how the world will change if Aurora’s vision comes true.

Subscribers to Changing Lanes will be notified when we go live, but please do sign up in advance here.

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Few people have seen automated-vehicle safety from as many sides of the table as Beuse: he spent nearly two decades as an executive at NHTSA, where he oversaw the US government's work on automated driving, then led led the safety team at Uber's self-driving unit, before joining Aurora. We'll talk about how a company proves that a truck with nobody aboard belongs on a public highway, and who should get to decide. Subscribers will be notified when we go live; you may also sign up here.

Everyone who talks about automated vehicles (AVs) eventually brings up the elevator.

Once upon a time, elevators used to have operators. In time, the technology to automate the job developed, but riders were too nervous to ride alone, so the job persisted. Then, the story goes, a strike in 1945 forced the issue, and the operators disappeared. The moral for automated driving is that even when the technology is ready, public fear will hold it back. To normalize that technology, all that it takes is to address that fear.

It’s a good story, and it’s one I’ve told myself. That’s why I’m chagrined to learn that, having investigated it more closely, it’s not quite true.

The accurate history of the elevator operator is that there was indeed a twenty-five-year gap between the first elevator that could run itself and the first office tower that did, but it wasn’t a strike that closed that gap. Four ordinary forces had to converge…

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This is a story I have been telling in Changing Lanes since its inception, and now, courtesy of Prof. Benjamin Shiller, we can attach some numbers to it.

Shiller, an associate professor of economics at Brandeis, has recently published a paper, co-written with Imke Reimers of Cornell: Will New Driving Technologies Change the Value of Public Transportation Investments? In it, the authors estimate how residents trade off price, time, and the discomfort of travel, then simulate a Greater Boston in which private self-driving cars are widely owned. The paper puts firm numbers on intuitions I have been pressing for years: that automation will induce more driving, push development outward, and wear away at transit ridership.

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To learn more, I spoke with Shiller on 16 June 2026. The transcript of our talk has been lightly edited for clarity.

Prof. Benjamin Shiller (provided photo)

Modelling a City of Self-Driving Cars

Andrew Miller: I went through some of your work, and I hope you don’t object to this, but I wouldn’t characterize you as an economist of mobility. The through-line in your work seems to be this: once upon a time there were markets, but they had a very fuzzy sense of who the consumers were. That’s all changed. Markets now are adjusting to a world where counterparties can have unprecedented understanding of who their consumers are, and how that changes the easy assumptions we’ve made. Tell me if that’s a fair characterization… and if it is, what are you doing with self-driving cars in Boston? How does that fit into your larger intellectual corpus?

Prof. Benjamin Shiller: I view my interests as somewhat broader: it’s generally how technological change will impact markets, and so much of my research focuses on more information being collected about consumers. In fact, it was based somewhat on this local law…

AM: When you say local, you’re at Brandeis, so you mean Boston?

PBS: Well, it was across all the towns in Massachusetts: if you were near public transit, you had to increase the amount of housing, or at least increase zoning, so that they could build more housing.

But I started thinking: do we really want to put all of this housing right by the public transit stops if self-driving cars are going to be very common in the future? In Massachusetts, there have been proposals to spend as much as $55 billion on public transit, which is about $8,000 per Massachusetts resident. And I think that makes a lot of sense if you’re anticipating that the life of these improvements is quite long. But if self-driving cars become common in five or ten years and people no longer want to take public transit, then maybe it’s a poor choice. It’s an empirical question.

AM: I certainly have strongly held takes on this, but for now let’s keep the focus on the paper. So you modelled what would happen when self-driving cars arrive in Boston at scale. And before we get into the conclusions, tell me about your methodology. How did you go about making the estimations?

PBS: It’s a challenge, because we don’t have widespread self-driving vehicle adoption, so you can’t use the standard methods from reduced-form economics. The way I did it is with a method common in industrial organization, where I estimated people’s preferences for particular characteristics of transportation.

I looked at how much people dislike a minute spent sitting passively on a commuter rail line, or in the future a self-driving car; how much they dislike a minute spent actively driving; how much they dislike having to transfer on public transit, and how much they dislike price. Once I’d estimated those, then I could create this new option, the self-driving vehicle, which would have the advantage of allowing you to sit there passively like you now can on a train, but could utilize the road network.

One complication that I had to account for in these counterfactual simulations is that if there are more vehicles on the road, that could increase traffic. And I know there’s research out there that suggests self-driving vehicles might use roads more efficiently, but I took the stance that they’re going to be like us and they’re going to increase congestion. And so I estimated, within sample, this shape of how congestion impacts the travel times in various concentric circles around Boston. I could then incorporate how an increase in road usage would slow down travel times. Thus, when I calculate a new equilibrium with self-driving vehicles, I can, and do, account for both the lower disutility of time spent driving and the increase in travel time due to congestion.

AM: I have always argued that self-driving is going to increase congestion. That argument rests on the Jevons Paradox, that if you make it less mentally taxing to drive, what you’ve done is reduced its cost, and if you make something less costly, people consume more of it, which means more driving and more congestion. It’s good to have a model that demonstrates this, rather than just an intuition.

PBS: I agree. Very recently I got Gemini in my car and I found myself much more willing to drive, because I can just have long conversations. I can ask it to look up e-mails, stuff on my calendar… driving is much less of a pain now. I was assuming that the disutility of time would be equivalent in a self-driving vehicle and on the commuter rail or on the subway, but I now think that it will be less painful to spend time in your own vehicle. You could do all sorts of things that you couldn’t necessarily do on a train, like have private conversations, maybe even shave or something like that.

AM: Well, for me, the smoking gun is that right now a Waymo trip in San Francisco costs more than a ride-hail trip, but people still take it. Part of that, I suppose, is luxury signalling. But the other part of it is that in conventional ride-hail, the presence of even one stranger, the driver, one who is guaranteed not to talk to you—which is not the case on a commuter rail—even this best-case scenario is still inhibiting in some ways.

In your own car, that’s set at the temperature you like, with seats that don’t have stains or crud on them, where you can listen to whatever you want… it is absolutely going to be much more comfortable. If I was constructing such a model, I would say that travel time in your personal vehicle is going to be more attractive than even a convenient ride on public transit.

PBS: Yeah.

What the Model Found

AM: That’s the methodology of it. And what were the findings? What’s the headline conclusion?

PBS: There were several findings, some I found obvious, and others surprising.

First, the basic finding: there was more congestion, as people drove a little bit more, but also moved further away from where they worked. I have different estimates from slightly different models, slightly different assumptions, but we’re talking about a 30%-to-40% increase in mileage. And I should note that this was just commuting to work, without accounting for midday trips or increases in delivery services. With self-driving trucks, it becomes cheaper to ship items, so we’d probably expect people to ship them even more.

The impacts on public transit were more surprising. I found a modest decline in public transit revenues and usage, a little over 10%. Why wasn’t there much of an impact? It seems to be congestion: as the benefits of driving increase—or the disutility decreases, when it’s not as painful to spend a minute sitting there passively—it nonetheless takes longer, so you’re spending at a lower disutility per minute, but nonetheless spending more time.

Interestingly, I also found that with even small improvements in public transit, like increasing the speed just a little bit, you could completely offset the reduction in revenue that was attributed to self-driving vehicles. So it was very easy to get usage and revenues back up to where they would be, if you only had modest improvements in public transit.

AM: Driving automation and its effects on transit is a complicated matter. In my view, the first thing to disambiguate is what you’re talking about when you say transit. Are you talking about surface buses, or are you talking about higher-order transit: subways, and commuter rail, and LRT?

PBS: That’s a great question. So in the research, I had public transit as its own category, and I didn’t distinguish between the different ones, but I was thinking about commuter rail and subway in particular. The commuter rail actually has a high price, and it caters largely to people with relatively high incomes. These, and to some extent the subway lines, where they’re not sharing the roads and having to struggle with increased congestion.

AM: There’s also the fact that the demographics of the usage and the periphery-to-central-business-district that’s being connected, you get fewer people using it for non-travel purposes, who are often bad actors. But yes, the key thing is that it has its own right-of-way. And what that means is that, if it’s a well-run system, travel time is faster than a car of any sort, and reliably so.

The Fleet Gap

AM: In your paper, you have modelled self-driving cars that are privately held. The model starts with the world as we have it, but then assumes that every car (to use my favourite metaphor) has a metaphorical ‘drive for me’ button on the dash. But that’s the only change: everyone still owns private cars, and uses them in the same way, as they do today. And the paper then considers how this new functionality changes our behaviour and what the emergent properties of the system become. That’s very much worth exploring.

But if you look at self-driving as we have it now and where it’s headed, it’s a different model, where most self-driving vehicles are robotaxis. So my book, or rather the one that I co-wrote with my two esteemed co-authors, was about two scenarios of the future: one, the one you’ve described, where everyone has a private self-driving car, versus one where everyone has access to a self-driving robotaxi fleet that’s cheap and reliable and convenient.

PBS: You’re saying the world where everyone owns their own vehicle is more likely?

AM: We would love to see a world where Waymo and its competitors are so ubiquitous that people drop the number of cars they own and just rely on robotaxis. But we think the path we’re on, absent severe policy intervention, is more like the world that I think your paper is describing, where private manufacturers just introduce self-driving capability and nothing else changes. That is what you are describing in your paper, which is why I think it’s good that you are modelling it. But I wonder: have you thought about the fleet model, and what implications it has, and if you did that model, how would it be different?

PBS: I’m glad that we think alike, especially since you have thought very deeply on this subject. Many people that I encounter argue that I should have taken the fleet model as the subject. And I did consider it. There are some challenges there; it’s harder to simulate the future— you must make assumptions about things like prices per ride and behavioural economics. But in the end, I agree with you, I think private ownership is more likely. I think that there are advantages to it, and that there are some real problems with the fleet model.

AM: That’s why I wanted to talk to you. I don’t need to talk only to people who agree with me—how boring would that be? Lay it on me.

PBS: There are big advantages to owning your own personal self-driving vehicle. One is just logistical: if you don’t live right in the urban core—so I’m thinking more like the suburbs—there’s a wait every time you want to catch a ride. Today, if I get an Uber, it’s not that long of a wait, but it’s still a hassle that I don’t necessarily want to deal with.

Additionally there’s some convenience to having your own vehicle. I have kids; I can leave the car seats in there. Maybe I want to keep certain things in it, my sunglasses, or soccer equipment if I’m a soccer coach; there’s an advantage of having it as a storage space too.

Artist’s conception

People also have a difficulty in parting with money. If you have a ride-hailing service or a fleet model, every time you catch a ride you would typically pay some cost. That’s the only way it would really work, otherwise the marginal cost is zero and people would overuse it, and that could be problematic when there’s a limited number of vehicles. So if every time you have to go through this mentally painful process of parting with money—because it’s very salient, when you open the app it has a price right there—I think people are going to be reluctant to do so. Whereas if you own your own vehicle, it might be more expensive overall, but when you take a trip you’re not really thinking of the price.

Another challenge is that the fleet model really struggles with surges and declines in demand. Now, if we think about self-driving vehicles, they could operate like Uber and bring more onto the road when there’s an increase in demand, but there’s this problem that the self-driving vehicles are largely built with a single purpose—a high fixed cost to create them. For Waymo, maybe it’s like $150,000, something like that. And so they’re incurring this large upfront cost, and if they’re only going to use it an hour a day or two hours a day during rush hour, it doesn’t necessarily make economic sense. So I don’t think they would necessarily want to provide a large enough fleet to provide all the rides needed during times of peak demand. And so then you have the situation where, if you don’t own your self-driving vehicle, either you’re paying through the nose when you actually want to be taking the trip, or you’re just not getting a ride when you really want it.

I think that’s a fundamental problem with the fleet model.

AM: Yeah, I agree. I wrote a whole piece, There Will Still Be Private Cars in the Future, drawing upon the book, and it makes those same arguments, that people will want them. The question is how many people are going to switch to the fleet model. Imagine I’m the CEO of Waymo or Zoox, I have to ask myself, do I size my fleet to the peak, or do I size it to the steady state? You’ve described very well: if you size it to the peak, that means you’ve got an awful lot of stranded assets at every time of day that isn’t the peak, whereas if you size for regular demand, your customers can’t use you during the peak when they really want it, and they’re mad at you. It is a tough problem.

Someone—not me, I think it was Reilly Brennan—has suggested that robotaxi fleets are sized to base demand, and human drivers jump in to handle that surge in peak periods, and when it’s done they take those cars off the road, because off-peak they can’t compete against the robotaxis. I think that is most likely.

How Transit Survives

AM: You’ve got some ideas about how transit is going to survive in this future. What do you think transit will need to do?

PBS: I think it needs to get more attractive in a number of ways. So, for example, in Boston, it needs to run more frequently. It would be nice if you could have a little more privacy, or have some ways to avoid disorder and other negative aspects. Economists often think about how you increase usage of something, and usually that’s reducing the price. So I tend to favour subsidizing some of these public transit lines, or even making them free.

If you do that, how do you keep people from misusing public transit and behaving badly on it? Maybe requiring a credit card to swipe in; perhaps you could track people and see if they’re behaving badly and revoke access. So I think a lower price, more convenient service, and then some way to handle the bad behaviour could make it so that the commuter rail, or the transit network in general, is something that can survive and still remain attractive in a world with self-driving vehicles.

AM: So I agree with most of what you’ve suggested. We should have lower fares, though I wouldn’t say zero; we should have more service. Anything you do to encourage people to use it not only makes the experience better, but it also builds a political constituency, so politicians want to fund it more.

Swiping a credit card is maybe not necessarily the first step. The first step is to have fare gates that you can’t hop over. Just getting fare-beaters out of the system—requiring a nominal fee to get in—it’s amazing how many bad actors that screens out. We had two natural experiments. One was COVID, where suddenly, the good actors had no reason to travel, and it was just bad actors on the subway, plus essential workers—and the essential workers then started leaving, because they couldn’t take it, it was too unpleasant. The other side of it is the congestion charge in southern Manhattan. Suddenly, the subways were crowded, crammed with people who formerly drove, and having all these law-abiding citizens on the system, things got way better. It is harder to abuse the system when you’re surrounded by other people.

PBS: And automation doesn’t just relate to cars; it also relates to public transit. There’s drivers, and so a fixed human cost per train, and that contributes to the lumpy service. If the public transit lines were automated, you could have a single train car coming every seven minutes, the same number of cars over an hour, but spread out. I’m sure this exists somewhere, but it seems like such an easy problem to solve. If we can make self-driving vehicles that work on paved roads, then it would seem so simple to make a public transit train that can drive itself on a train track.

AM: Yeah, rail is the easiest mode to automate, because there are only two directions to go: forward and back. Later this week, on Thursday [ed. note; out now!], I’m publishing a paper with the Institute for Progress, as part of their Transit Abundance Playbook, arguing that what we really need to do to improve public transit in the United States is automate it. And there’s one—not even a law, a subsection—Section 13(c) of the Mass Transit Act says you cannot automate without making every single worker whole. And all Congress needs to do is strike that one provision. The only automated system in the United States is Honolulu, because they built it to be automated from the start; there were no workers to displace. Nowhere else has done it, because it’s just too expensive.

PBS: That’s really unfortunate, because worker displacement is how we develop economically, right? If we just protect workers—an example I give in my book is that 200 years ago, 80% of US workers worked on farms; now it’s 1%. That’s because of automation, and if we still had 80% of us working on farms, we wouldn’t have all this other stuff. So yes, it’s painful for people to lose their jobs, but over time they find new jobs, and that’s how progress happens.

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AM: Well—just so that no one thinks that I’m picking on Americans—Waymo wants to come to Toronto, but the mayor’s press secretary said explicitly that Waymo is only welcome in the city if it can show that no ride-hail driver will lose their job as a consequence of Waymo arriving. There was a time when everyone got around by horse, and then the car came along, and everyone who was a stable hand or a farrier lost their job. But do we think that was a bad outcome? I don’t think so.

In fact—I’ll put on my economist hat: just buy them out. Figure out how much money you’re going to save, figure out what they will accept; it’s like, “All right, leave aside the future generations of workers that won’t have jobs, what will it take to make this generation whole? We’ll buy you out.” Given those parameters, we could find a deal worth taking. We just need to find a counterparty who will accept it.

This has been a wonderful conversation. Benjamin Shiller, thank you for your time.

By way of postscript: Prof. Shiller is also the author of a recent book, AI Economics: How Technology Transforms Jobs, Markets, Life, & Our Future, which trains his economist’s gaze on what artificial intelligence will, and will not, change. I expect to review it in a future issue, but if the topic interests you, don’t wait on me, order your own copy now!

The Transit Abundance Playbook, various authors, published by the Institute for Progress, June 2026

Italy is not an easy place to build a subway. Though not a poor country (it has the eighth-largest GDP in the world), it is poorer than the United States, and it suffers a massive debt-to-GDP ratio, severely constraining its fiscal flexibility. The density and antiquity of its cities means that tunnelling must contend with challenging work constraints, unhelpful soil composition, and archaeological protections. Notoriously, until a few decades ago its public-works contracts were utterly corrupt, with bids rigged and bribes paid throughout: the Mani Pulite (‘Clean Hands’) investigations of the early 1990s arrested some 4,800 people and placed more than half the national parliament under suspicion.

Given all of this, it’s no surprise that Milan and the smaller northern cities build subways (metros) for about $300 million per mile, and the ruins-riddled centre of Rome builds for about $800 million per mile.

The United States has every advantage Italy lacks. It is the richest country in the history of the world, with the deepest capital markets and the best engineering schools, a civil service largely free of corruption, and a century-old talent for building transit; before the war, it laid more streetcar track than any other nation on earth.

It is therefore surprising that it builds rail rapid transit for around $800 million per mile on average, i.e., it pays on average what Italy pays in its most-difficult environment. And in New York City—which builds the most expensive transit in the world—Americans paid roughly $2.6 billion per mile for the Second Avenue Subway.

To be specific: per mile, New York’s Second Avenue Subway cost more than ten times what one global peer city, Madrid, pays, and NYC’s East Side Access, at $11.2 billion, opened as the most expensive railway station ever built.1 As a consequence, despite its wealth, the country now builds very little transit indeed. Exhibit A is California’s high-speed rail line, whose projected cost has ballooned from $33 billion to more than $126 billion; with federal funding now clawed back and not a mile of usable track laid, whether the line will ever be built is an open question.

The richest country in the world, with all its technical capability, builds less transit and pays far more per mile than peer countries with far fewer advantages. Why?

That puzzle is the spine of the Transit Abundance Playbook, a collection published by the Institute for Progress on 17 June 2026. It consists of fifteen short essays by transit practitioners, researchers, and advocates, each aimed at naming and solving one driver of the USA’s exorbitant transit-construction costs. Most reach for a federal lever to fix it, because this is a ‘playbook’ for the US Congress to run to bring American transit up to a global standard.

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My readers should be advised that I’m no neutral third-party reviewer; I wrote one of the Playbook’s fifteen essays. (More about it later.) That alone would make me a strong proponent of the book and its prescriptions. But I have more reason than that to recommend it.

Before I became the writer of Changing Lanes, I worked in the space the playbook describes. As a public servant, I spent four years planning a new bus rapid transit line in western Toronto (across Mississauga): I wrote the project scope, procured a consortium of planners and engineers, and led that team as we drafted, consulted the public upon, and ultimately obtained political approval of the project plan. Later, I consulted on several transit projects, both as part of a major firm and as a one-man shop.

And given that experience, I say that the Playbook is right. The problems it identifies are real; they are the most important ones to solve; and the solutions on offer should be implemented.

Beyond that, I want to say what the Playbook is too polite to make plain, and name the root of the problem. What is holding back American transit? The Introduction states that “there is no single cause”. On the contrary, I think that there is, and that we can see that cause at work behind almost every individual contribution. Knowing the enemy is vital to fixing the problems holding back American transit: not only its construction, but its operation too.

That enemy’s name is defensive proceduralism.

Rules as Tools, or as Weapons

The key word here is defensive. Let’s define proceduralism as the tendency to establish rules in advance for how to scope, design, and deliver a project, and for what kind of input the project will accept, from whom, and how. This is a good thing, allowing everyone involved to know the game being played and how to play it. Italy’s experience demonstrates the value of proceduralism. The country enjoys very low per-mile transit construction costs today because, to combat corruption, it relies heavily on open procedure: published price lists, an anti-corruption authority, bids scored on merit, and internal state capacity such that civil servants are able to run a project themselves. These measures aim to prevent corrupt practices, and have the helpful downstream effect of keeping costs low.

So Italy has proceduralism. What is the USA’s problem, then? Not the presence of rules, but their aim. In Italy, the rules aim to deliver projects on time and on budget. In the USA, the rules aim to stave off lawsuits or blame. That is the American disease, and once you look for it, you will find it behind nearly every contribution in the collection.

Start, for instance, with Transit Projects Need a Single Decision-Maker, written anonymously (!) by someone who “works in project delivery for a public transit system”. Perhaps because they are anonymous, the author of that piece states the case more plainly than the authors of the introduction dare to. American institutions are unusually open to litigation, everyone understands that judges rather than elected officials or civil servants are the final arbiters of what is permitted, and that those judges are not trained as engineers or planners, but rather to determine whether the rules were followed. Agencies, knowing this, lower their ambitions and spend their days documenting decisions rather than making them. In such an environment, procedure is less a tool for building and more a weapon to stave off lawsuits. Environmental review under NEPA or CEQA is one example of this; so are rigid sequencing gates, or lowest-bid mandates that exist mainly so no official can be accused of favouritism.

Consider also procurement, as Alon Levy (whom Changing Lanes admires deeply) writes in We Should Know How Much Transit Components Cost. American agencies prefer to construct their transit projects in lump-sum contracts. Why do they do this? So that when cost overruns appear, as they will, the contractor must absorb them, keeping the project on budget and hence the agency free of blame. That’s defensive procedure doing exactly what we would expect, and the result is exactly what we would expect as well: bids are inflated dramatically to cover the risk being transferred. On top of that, there is the change-order racket. Contractors win bids by submitting low, and then any change that comes up after award is a change order, and the opacity of their costs—lump-sum contracts mean that per-component and per-activity costs are kept secret as commercially sensitive—allows for maximized change-order values, to the tune of 20 to 50 percent. The fix is not less procedure but different procedure, namely the itemized, public pricing Italy and Spain use, which Levy estimates would cut 15 to 20 percent from a typical project.

The thread runs everywhere. It’s in Eliminate Redundant Subway Cross-Passages, where Brian Potter shows that American tunnels carry roughly twice as many cross-passages as European ones, because the National Fire Protection Association (NFPA) 130 fire standard demands one every 800 feet against Europe’s 1,640, even though the NFPA concedes it has no technical substantiation for the spacing. The requirement is merely defensive, a margin of safety nobody can be blamed for adding.

The same instinct shows up in Fast-Track Democratically Approved Transit Projects, in which Hayden Clarkin describes projects that voters have already approved at the ballot box being sent through years of NEPA review, not to inform a decision the public has made, but to hand opponents a second venue in which to undo it. The defensive party here is the agency: it dares not waive or even shorten the review for a project voters have already approved, because an under-reviewed approval is exactly what draws the lawsuit. So the agency runs the full multi-year process to protect itself, and that very thoroughness is the weapon its opponents pick up.

Rules First, Build Second

From my days as a transit-project lead on the public side, I remember the order of operations: my job (and that of everyone I worked with) was to follow the rules first, and bring the project in on time and budget second. Nobody wanted delay, but the facts of the matter were that breaking a rule, no matter how small, was a thing one could be punished for; breaking the schedule or the budget was not. In such environments, the rational move is to give up decision-making power, since that means also dropping the burden of blame.

In Put Transit Staff in Charge of Their Own Projects, Paul Lewis traces why American agencies hollowed out their own expertise at transit building: agencies lean on consultants as decision-making buffers, hiring outside firms to validate controversial choices and supply political cover, a habit that reinforces risk-aversion and diffuses accountability so that no one inside is answerable for anything. A staffer who uses judgment and is wrong owns the mistake; one who can point to a consultant’s report does not. I have worked as a consultant in this world, and out of respect for everyone involved, I will say only that Lewis is absolutely right.

Four of the collection’s pieces map this same instinct to seal off every angle of attack and to pay for the invulnerability in taxpayer money and additional years spent. In Get the Best Value in Transit Procurement, Anthony Potts shows that lowest-bid mandates—defended as a guard against favourtism and graft—instead shut out the best-value bids. In Focus Capital Investment Grants on Improved Project Delivery, Stephanie Pollack shows us a federal grant process grown so rigid that its own rules now obstruct the timely, affordable delivery they were written to secure.

The remaining two turn on environmental assessment. In Let Agencies Do Their Own Environmental Review, Jamey Tesler shows agencies compiling reams of paperwork merely to certify that a routine project has no significant environmental effect, a status that all but a handful of projects plainly qualify for. Tesler’s remedy is to let agencies self-certify these routine findings. As it stands, the documentation protects not the environment but the FTA’s decision from challenge, and gets done in full even when the answer was never in doubt. In Let Transit Agencies Buy Land, Aidan Mackenzie shows agencies unable to buy land or move utility lines until NEPA review is complete, to avoid prejudicing the findings. That process takes on average 5.7 years, so they end up paying more for the land, and sometimes routing around it entirely.

Artist’s conception, after original art from the Playbook

Public servants still have some capacity for discretion, and some use it. On my own project, as part of the engagement process, one party whom I had a duty to consult tried to bill the project for the time and capacity spent on its own due diligence.2 I figured the demand was a bluff, refused it, and the request went away. But I remember that stand vividly today because it put the project, and my leadership of it, at risk; the party might have come back with a lawsuit. The smart thing to do for my career would have been to pay, write a memo explaining the situation, and move on. I didn’t because I found the demand offensive, but I can’t blame other leaders who decide the other way, their prudence outweighing their outrage.

The better path, of course, would be to draw the rules about consultation narrowly enough that leaders are never put in that position.

Fifteen Problems but One Foe

The Transit Abundance Playbook offers an institutionalist case for building transit more cheaply. The modesty of its introduction insists “there is no single cause” and lists the drivers as equals: overdesign, poor planning, veto points, permitting, thin capacity. That is sound coalition-building, but in my view it undersells the book’s best insight, the one its anonymous single-decision-maker essay says out loud: there is a single cause, namely the fear or being blamed, exacerbated by the litigiousness of Americans and the unusual latitude for American courts to entertain it.

Seen in that light, defensive proceduralism is the problem. Anyone who funds, plans, builds, or votes on transit should read this book, and should read it as one argument, that transit agencies need the expertise to run their own projects, the power to get them built, and the freedom from interference by opponents and rent-seekers.

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In closing, I’ll note that defensive proceduralism shapes not only how America builds its transit, but also how it runs it. My own contribution to the collection, Close America’s Transit Automation Gap, is therefore an outlier in that regard, because it’s less about how to build more cheaply than about how to build a system that will be cheaper to operate. I encourage readers of Changing Lanes to read the whole thing (it’s about the length of a typical issue).

My argument there is also about defensive proceduralism: the reason that American transit agencies have not retrofitted their systems for full automation is a sixty-year-old labour-certification rule. That rule was drafted in 1964 to solve a real problem, but one that was solved by the end of the decade. It wasn’t removed, and not only remained on the books, but became supercharged in the 1970s as the national government became a major funder of transit operations. The result is that while the rest of the world (including Vancouver but not, to my chagrin, Toronto) automated its rail transit, the USA largely has not. Rectifying that failure would save hundreds of millions in operating funding, each and every year.

The Institute for Progress has done Americans a great favour by showing how transit construction could be improved. But there is also need for another playbook that shows how transit operation could be improved as well. If the Institute is looking for a new project, it could do much worse; I can think of a few ideas legislators would benefit from hearing.

Rhishi and I are kindred spirits. We are both fellows of the Roots of Progress Institute; we have both worked in consulting, operations, and Alphabet-sponsored Big Tech across a variety of roles; and are both now writing about how automation will change the world.

Rhishi is intimately familiar with sectors I know less well, notably mining and agriculture, and I learned a great deal from this piece. I am sure you will as well!

Waymo has already driven close to 200 million miles and 20 million rides without a driver. Waymo is already operating in multiple metro areas in the United States, with more than 20 additional cities coming up next, including London and Tokyo. Waymo has opened freeway operations to paying riders in Phoenix. Tesla has a limited number of robotaxis running in Austin.

While Waymo’s achievements are significant, other sectors like mining, industrial security, and agriculture have beaten them in the autonomy game a few years ago.

Hundreds of autonomous-haul trucks have moved millions of tons of rock across Australia and Latin America for more than ten years. Autonomous ground and air units have patrolled airport perimeters at multiple airports for a few years now. Agricultural machinery giants like John Deere and CNH have been pushing for autonomous corn and soybean systems to become fully operational in the next few years, with some operations, like tillage and grain cart management, already working autonomously.1

These domains reached driverless operation at scale before the public-road robotaxi did.

Now, consider Phoenix, where multiple robotaxi companies are operating. One of them, Waymo, provides a robotaxi that drops a rider at the airport. The fence line the Waymo passes on the way in has been patrolled by autonomous ground and air units for the better part of a decade. Two autonomous systems are operating within a mile of each other, but they arrived on two completely different timelines, with Waymo the newest.

In the hierarchy of operational autonomy, the robotaxi is the latecomer.

The rate-limiting factor for adoption is not AI capabilities. It is the four conditions that robotaxis face, each in the most difficult form possible. These are operating environments, liability regimes, unit economics, and operational maturity. These circumstances have had and will continue to have the greatest impact on adoption rates and scaling.

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The Road Most Taken Is the Hardest

First, operating environments.

The Pilbara region of Western Australia has a population of only 60,000 people across 500,000 square kilometers, a density of 0.1 people per square kilometer. It sits atop enormous iron ore deposits. The haul roads to and from the mines are private, fenced, and mapped to the centimeter. A 410-ton Caterpillar 797F is four stories tall and has tires taller than a person. It has been hauling rock there autonomously and nearly continuously since 2013. Since then, Caterpillar’s global autonomous fleet has moved more than 8.6 billion tonnes.

It is difficult to visualize 8.6 billion tonnes of rock. For context, the granite George Washington at Mount Rushmore weighs roughly 4,000 to 5,000 tonnes. The global autonomous fleet has moved enough material to carve 1.7 million of them!

Agriculture follows the same logic in its own low-density environment. John Deere unveiled their fully autonomous 9RX tractor at CES 2025. The tractor is a behemoth with tires bigger than human beings and boasts an 800-900 horsepower engine. Deere already runs an automated tillage machine and hopes to achieve fully autonomous corn and soybean production by 2030. The farm reached driverless operation because it operated in a more controllable environment than a street.

When I visited Raven’s (part of CNH, the world’s second-largest agricultural equipment manufacturer) research facility in Sioux Falls, South Dakota, about four years ago, I had the privilege of seeing the testing of an automated grain cart solution in a real field. In 2025, CNH launched its automated grain cart solution as a commercial product.

The operating environments for mining and agriculture are well defined and ideal for the adoption of autonomy. They are bound, mapped, well managed, and almost empty of obstacles, especially of the human kind. Even though a mine and a farm have more dust and dirt to deal with, the operating environment on public roads is much more challenging, with unpredictable human behavior, gnarly traffic conditions, and changing weather.

A leafy-green field in Yuma, Arizona. Notice the well-defined rows and almost flat fields devoid of humans or other traffic (photo by the author)

A robotaxi has to operate in one of the hardest contexts. Waymos and Teslas have to navigate public roads shared with pedestrians, cyclists, and human drivers in legal environments they don’t control.

The mine and the farm solved the issue of autonomy by changing the road. The robotaxi has to solve autonomy without that luxury.

Who Owns the Risk?

The second factor shaping where autonomy flourishes first is liability regimes. Andrew argued here a few weeks ago, in “Robotaxis Companies Must Always Pay, that robotaxi operators should accept full operational liability. The clean assignment of responsibility is what lets deployment scale.

Mining is the proof of that concept.

In a mine, the operator and the customer are often the same billion-dollar entity, and workplace-safety law already assigns the risk to that operator on a private site. The mining industry answered the liability question before the trucks arrived.

Farming sits in between. Liability is shared among the manufacturer, the software provider, and the operator. It is less settled than mining but far clearer than the public road.

On public roads, industry and regulators are still litigating this question on a case-by-case basis. As Andrew mentioned in his piece, Benavides v. Tesla was a recent, expensive example.

Autonomy scales fastest if the liability structure is settled. Mining’s liability structure was settled by default.

The Math Has to Work

The third factor is unit economics.

Autonomy went to mining first because the economics were overwhelming. A mining customer runs a fleet worth billions, pays a heavy premium for labor in remote locations, and runs 24/7. The automation of haulage fleets is the chosen path for much of the mining industry in Australia and Latin America.

Removing the cab operator compounds across every truck, every shift, and every commodity. This situation is especially true in Western Australia, where the odds of finding a random human are low, and the odds of finding someone willing to work in the difficult and dangerous mining environment are even lower.

I am working on a project with the Western Growers Association to help them figure out how to automate the harvesting of iceberg lettuce. The economic case for autonomous vehicles is strong for specialty crops like this one; more than half the cost of getting your bagged salad to you is due to manual lettuce harvesting. Access to labor at economically favorable prices is becoming increasingly challenging, making the economic case for automated harvest stronger every day.

Airport perimeter, warehousing, and logistics security tell the same story from the other end of the size scale. An autonomous security unit removes costs associated with hiring and churn, skill-set inconsistencies, and the need to reach hard-to-access areas. For example, Asylon’s DroneCore pairs aerial drones with ground quadrupeds and reports thousands of dollars in annual savings across Asylon’s platform, which has completed more than 250,000 security missions (as of 2025).2

A robotaxi’s per-ride economics, by contrast, are still converging as companies try to optimize product development and operating costs and match them with customers’ willingness to pay.3 The question of “when will Waymo be profitable?” remains valid.

In mining, security, and agriculture, that question was much less in doubt.

Doing the Reps Helps

The final factor to consider is operational maturity.

When building autonomous systems that operate in real-world environments, it takes time to learn and handle edge cases. When I was working on building AI-powered selective weed-spraying technology, we spent months in the field testing the algorithms under different conditions, yet still didn’t make much progress getting it to work. The graveyard of robotics startups is massive, with many companies that couldn’t ‘get enough reps’ to make the technology real-world ready.

Caterpillar’s MineStar Command for Hauling went commercial in 2013, runs 24/7 across six commodities, and reports zero lost-time injuries attributable to autonomous operations. Caterpillar has had 13 years of experience in fleet management, exception handling, and maintenance, which are the unsexy parts of the business. The reps help identify unforeseen issues and build scalable, resilient, and efficient systems that help you manage and run a business, rather than just being excited about cool technology.

Waymo’s genuinely impressive scaling has happened mostly in the last 24 months. The robotaxi’s autonomy stack may be more sophisticated, but the operating discipline around it is younger. Waymo and other robotaxi companies have used simulation to “learn” and expose unseen use cases, but real operating environments still throw surprises.

Autonomous tillage equipment and grain-cart solutions have undergone trials in real-world settings for many years before entering commercial production. By contrast, right before Christmas last year, a power outage in San Francisco caused many Waymos to stall at intersections, block arterial roads, and, according to at least one city official, impede emergency vehicles. It appeared as if Waymo robotaxis compounded the problems caused by the blackout.

In physical systems, that gap matters more than people expect.

Why Is This Reframing Important?

When we think about autonomous vehicle adoption, we need to reframe what makes adoption happen faster and in more domains. Once the technology issues are resolved, the adoption curve will be driven (pun intended) by factors such as the operating environment, liability, economics, and experience.

Why does this reframe matter for people who think about AVs for a living?

It matters, because if factors like operating domain, risk infrastructure, unit economics, and experience gate autonomy are considered, then the interesting investment question isn’t only “when will the robotaxi be profitable.” The interesting investment question is also where innovators can apply autonomous technology in an economically sustainable and safe manner.

Robotaxis are a major domain that lacks the advantages of a controlled operating environment, clear liability regimes, favorable economics, and years of experience.

For any domain, the differentiation will not come purely from raw model performance. It will come from an operational track record, edge case management, and deep customer relationships.

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For most of the last decade, mining autonomy, robotaxis, autonomous tractors, and security robots were separate engineering worlds with little in common. But now a common technical stack is emerging across all of them, which includes foundation models, vision models, imitation learning, and diffusion policies for control.

The same underlying machinery that drives a robotaxi is starting to drive a tractor, a quadruped, a humanoid. When the stack converges, the lessons from the domains that solved autonomy first will become transferable to those still catching up, whether it is mining’s operating discipline, security’s unit economics, or agriculture’s environmental control.

The story of Physical AI and automation is complex, with multiple threads spanning robotaxis, mining, security, industrial applications, transportation, and many other domains.

Paying attention to technology issues is extremely important. It is also exciting and exhilarating, as smart teams and organizations solve one difficult problem after another, like Mark Watney in The Martian. But if we are interested in seeing these technologies scale and actually have the positive impact they promise, we will have to pay attention to the other, non-flashy parts of the autonomous adoption equation.

Waymo is not leading the autonomy party. It just showed up to join it.

Which domain will quietly solve autonomy next, and who will notice before the market does? I plan to pull this thread every other Wednesday on Jacquard’s Loom.

This has been a Changing Lanes guest post by me, . I am a solopreneur working on automation, physical AI adoption, and digital transformation in legacy industries. I have experience working at Google X, Amazon, and multiple startups in supply chain, automation, and AI.

My Substack newsletter, , is for anyone curious about how automation and physical AI will impact our daily lives. Jacquard’s Loom will take a holistic approach by examining the how, what, when, and why (or why the hell not?) of automation and physical AI.

I would like to thank for giving me the opportunity to write this guest post for Changing Lanes, and for his honest feedback on earlier drafts.

On Wednesday, 24 June at 1200h ET, on the second Changing Lanes livestream, my guest will be the foremost American authority on regulating automated driving: Professor Bryant Walker Smith of the University of South Carolina. Smith helped develop the SAE’s “five levels” of driving-automation taxonomy, and earlier this year he testified to Congress on how the United States should regulate self-driving. Subscribers will be notified when we go live; you may also sign up here.

And on Tuesday, 16 June, i.e., in five days, the subscription rate for Changing Lanes goes up, rising from the current rate of US$10/month or US$100/year to US$13/130. This means that now is the best time to change your subscription from free or monthly to annual, since switching now locks in a full year of content at the best possible rate. It’s as easy as clicking this button!

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Today I’m pleased to offer readers my interview of Eric Lombardi, a candidate for the leadership of the Ontario Liberal Party, and (if he succeeds) for the office of Premier of Ontario. The material that we discuss is separated by caption, as follows; readers may wish to skip ahead to their favourite subjects.

• Managing Decline or Building Abundance

• Ribbon-Cutting vs. a Manufacturing System

• The Housing Theory of Everything

• Bringing Down Construction Costs

• Rail: Speed, but Also Coverage

• Road Pricing

• Driving Automation

• Rural Areas, Remote Areas, and the North

• Energy and Nuclear

• In Conclusion

The reason I am giving readers permission to skip ahead is because this piece is lengthy, about four times the length of a typical Changing Lanes piece. But I am nonetheless presenting it in full, for two audiences.

If you live in Ontario, you will find it interesting as a vision for the province’s future: one potential leader’s account of how to build a more prosperous province. If you live anywhere else, you will also find it interesting, as an example of what the abundance agenda looks like, translated into a campaign frame, and defended by someone who aims to win votes with it.

What follows is a conversation about why housing costs what it does; a theory of why Toronto builds transit at four times the cost of Paris; a case for high-speed regional rail, road pricing, and driverless cars; and a plan to make people consume more electricity rather than less.

Changing Lanes is a non-partisan newsletter, and we do not endorse any candidate of any party. But we are interested in any candidate who thinks that innovation, technology, wise policy, and good institutions can make the future better than the past. Lombardi seems to believe this, and to have thought deeply about how the abundance agenda can succeed in his particular context. I am confident that readers of this newsletter will find what he has to say interesting.

Lombardi and I spoke on 1 June 2026. The transcript of our remarks has been lightly edited for clarity.

Managing Decline or Building Abundance

Andrew Miller: It’s a pleasure to speak with Eric Lombardi, the founder of More Neighbours Toronto, Toronto’s foremost YIMBY organization. He has stepped back from that work to explore the leadership of the Ontario Liberal Party — so there’s a chance that, in a few years, he could be the next Premier of Ontario. I won’t put words in his mouth, but it seems to me that Lombardi’s interests are very abundance- and YIMBY-coded, which is the very philosophy we endorse here at Changing Lanes. So I reached out, and he graciously agreed to sit down and talk about his vision for mobility in Ontario. Eric, it’s a pleasure to speak with you. Thank you for agreeing to speak with me.

Eric Lombardi: Andrew, it’s a pleasure to be here. My exploratory will soon become a campaign, so stay tuned over the next week or two — perhaps by the time we release this, I’ll be formally in the race. [Note: Lombardi formally declared his candidacy on 9 June 2026, a week after we spoke.]

Eric Lombardi

AM: That’s breaking news. It’s no longer an exploratory campaign… it’s happening! Very exciting. Let’s talk about your vision for Ontario. I think the place to start is what I’d call the spiciest thing you say: that Ontario is managing decline. Long-time readers of Changing Lanes will know I’m against what I call genteel decline, which is what I think a lot of what happens in Toronto and Ontario amounts to. I wonder whether we mean the same thing, but I won’t tell you what I think. When it comes to how people and goods move around this province, what do you mean by decline, and what’s the alternative?

EL: What I mean by decline is just the real facts of how our economy has performed over the last 25 years. Once you remove immigration and inflation, our economy has been one of the worst-growing in the entire developed world. We’ve had enormous productivity challenges, and over this time we’ve seen increasing dysfunction in the state’s capacity to deliver the goods and services that produce a higher quality of life. The result is that living standards for ordinary people have fallen. And the biggest part of this is how much of the burden has been placed on the next generation, in the form of what I call a milestone recession: the modern economy has made it increasingly difficult for young people to hit the traditional milestones of life — finishing school, getting a good job, buying a home, starting a family. All of them are shifting further into the future. While this is a problem globally, much of it can be explained by economic trends specific to the province that have worsened those global factors.

We also need to understand how decline gets managed by politicians. It’s been bipartisan across the spectrum here in Canada: the adoption of communications-forward politics rather than outcomes-forward politics. So even as things function less well, there’s always an air of optimism — we’re doing things, we’re building things, we’re growing the economy, we’re creating jobs. But the numbers don’t hold up to the language.

Ribbon-Cuttings vs. a Manufacturing System

AM: I spent eight years with the Government of Ontario as a civil servant, and I came away with a certain cynicism. The attitude in that era — I won’t point fingers at any particular premier — seemed to be that our job was to write a cheque, so we could then hold a press release or an event and say we’re spending X tens of billions, Y hundreds of billions, on this problem. And once the press release was out, that was it. Whether the money achieved any of its goals, whether it was even the right thing — none of that mattered. What mattered was being able to say you’d done something.

EL: In politics we love to announce big cheques, and we like to talk about all the jobs we’re creating. We don’t like to talk about the jobs we’re destroying by taxing those cheques to pay for the spending. This thinking about trade-offs has become almost entirely absent from our politics, and that’s one of my motivations for running. What upsets me, specifically in infrastructure — and we’ll talk a lot about transportation today, but it’s just as true in energy — is that we think in projects, because a project is something a politician can announce. And often the projects we pursue don’t start from a technocratic ranking of what would optimize value for money; they start from what politicians want to draw on a map to please which voters, and where.

So instead of thinking about how we build as a project, I want to orient Ontario toward thinking about how we build as a manufacturing system. What are the networks we want to reach in 25 or 30 years? Then how do we standardize designs — stations, below-grade, at-grade, viaduct-based rail, BRT — so that we’re consistently building toward a target over time? That’s how the great rail infrastructure systems around the world are built. Then you prioritize which projects and extensions come next. And the lever for government isn’t which projects get pursued; it’s how heavy a foot we want to put on the gas by capitalizing that process. That’s a very different perspective on growth and transport than what we see today.

The Housing Theory of Everything

AM: I want to get into that closely. But before we do — you mentioned energy, which is one of our minor themes here at Changing Lanes, so if you want to talk nuclear or renewables, we can. Before that, though, the area you’ve been strongest on, and that we spend the least time on here, is housing. So let’s warm up with that. Something I like to say — I didn’t invent it — is that housing policy and mobility policy can’t really be separated. You can’t build housing without a plan for how the people living there will move, and you can’t build a mobility system without thinking about the jobs, homes, and commercial uses you’re trying to connect. What’s your housing vision, and how does it relate to your transport vision?

EL: To be cheeky, I’d say you actually can separate them, but you create a lot of problems for yourself, and that’s part of why we are where we are. Just because you can doesn’t mean you should. Getting ahead of transportation and infrastructure policy to enable housing is incredibly important. But let me start with the big picture, then turn to my housing agenda.

I subscribe to the Housing Theory of Everything, which many of your readers will have seen in Works in Progress, out of the UK, a few years ago — I think it was Sam Bowman [Note: it was, with John Myers and Ben Southwood]. When an increasing share of people’s income goes to rent — whether that’s paying a landlord or paying higher interest on a mortgage to afford a suitable home — they’re not saving, they’re not investing, and they’re not spending. So the economy is deprived of all the healthy activity that drives growth, competition, investment, and higher wages. When you look at what’s happened with housing over the last 25 years, and then at our slow growth and the unhappiness young people express, these things are related. If you have one dial to twist to re-platform the province for growth, it’s fixing our broken housing system.

How do you do that? There are five areas. First, the rules around permitting and land use. Ontario municipalities set land use, so even though Mississauga’s and Toronto’s zoning codes look similar on the surface, you have independent policymakers deciding what studies a multi-family project needs, what’s allowed in each designation, all the bylaws. It’s too complex. I’d provincialize the setting of rules and make municipalities the appliers of rules — “provincial residential zone two applies in these areas” — rather than reinventing the wheel 440 different times. The same is true of the application process itself: in the GTA the average time to get a building permit is over 20 months; in places like Denmark it’s closer to 60 days. That’s not a sign of a functioning system. It’s a sign of a system so complex and discretionary that, even when all the rules are followed, people still believe the outcome is being corrupted. That’s a big problem.

Second is the building code. A lot of what we build is ugly and uncanny. Our code doesn’t distinguish between a four-storey building and a 60-storey one. If we reformed it — single-egress design, European elevator standards, updated fire-code standards for the built form, the way housing gets packaged — we could produce much nicer layouts at much lower cost, especially for the new urban places we’re trying to build. This is something a lot of YIMBYs miss: beauty should be a consideration in how we grow. When we make the case for growth, we should explain why it’ll be nice and beneficial for people — not just “housing is housing, it doesn’t matter how ugly it looks.” It does.

Third is taxes. American readers may not appreciate how much tax Ontario puts on new housing; there’s nowhere like it in the world. Until recently, when governments started to address it, housing was taxed more than cigarettes or alcohol — more than any other product or service in North America, to the tune of about 30% of the cost. I’d abolish all taxes on new housing construction, whether it’s land transfer tax (a tax on the exchange of housing), development charges (an upfront tax on every new home), or HST (a sales tax). These are unproductive taxes that create a like-for-like price gap between an existing home and a new one, which effectively forces buyers to speculate that existing-home prices will keep rising to justify buying new supply.

Fourth is non-market housing, which has been an abandoned part of the mix in Canada for about 40 years. We’re starting to come back to co-housing, co-operatives, not-for-profit and public housing. All of these need to be part of the mix and can complement private-market development. We should be talking about somewhere between 10 and 20% of all new housing being non-market in some form.

And fifth — we have to do right by young people, and by those who bought in the last 10 years and might face economic insecurity if house prices fall. For young people, we need to make housing affordable again. I think we should allow smaller down payments for first-time buyers — 10% on a CMHC-insured mortgage — to lighten that burden. If you’re young and could retire before you’d pay off your mortgage, you should be able to buy with a longer amortization, say 35 or 40 years, because you expect higher income later in your career; when you remortgage, you can always move to a faster payoff. Sometimes, when you’re trying to start a family, affording the home to start it in matters more, and that can’t be ignored. I’d also have the government give zero-interest loans of up to 5% toward the down payment for families with kids under six, because home ownership is something most families should be able to access and aspire to, and it’s good for kids and for society. And I’d give targeted renter relief to people under 35 and to families with kids under six, so they can save for that investment. We have to make it easier for young people to buy that first home earlier, if we want them to be able to think about starting families earlier too.

Then we have to do something for those who bought in, say, 2020 and might be out of equity, or might not have enough saved if they need to move for a job. You don’t want them trapped. We need to prevent downward mobility so people have economic confidence going forward. And if, as Premier, I’m going to say we need lower home prices for housing to be affordable — which no politician in this country seems willing to say — then I also need to be willing to say to people who couldn’t wait for government to make the right choices, and who now find themselves out of equity or in a debt trap: we have solutions for you, you have a great future, we’ve got your back.

Bringing Down Construction Costs

AM: I didn’t interrupt you there, because I wanted readers to see just how in the weeds you are on housing. You’re not a fly-by-night candidate on this; you’ve thought very deeply, and you’ve got a strong program. But given all that, what’s your thinking on mobility? We’re going to create a lot more infill housing and smart new communities — tell me how we’re going to move all the people who live in them.

EL: There are a couple of problems to solve. The first is how we build. Ontario has become uniquely inept at building infrastructure, both on time and at globally competitive cost. I know some of these challenges exist in the United States, and more broadly across the Anglosphere —

AM: Let me interrupt to say that I know you’re very influenced by the work of Alon Levy and the Transit Costs Project. Some Changing Lanes readers will know their work. This ineptitude is new. There was a time in my lifetime when Ontario, and Toronto, were some of the best builders in the Anglosphere on a cost-per-kilometre basis for new rapid transit. In your view, what changed? What’s the problem, and how do we fix it?

EL: Number one, we shifted from largely public-led infrastructure development to consortium-based public-private partnerships. When the TTC managed delivery of the Sheppard subway, or the Yonge North extension, we were closer to $300–400 million per kilometre — and we had nice stations that people thought were overdone and a waste of money. If we could get back to that inflation-adjusted value, it would be a miracle, because with the Ontario Line — and even the Eglinton LRT, which isn’t really rapid transit — we’re closer to $800 million, and over a billion dollars per kilometre, a million dollars a metre, to build now. That’s crazy. Politicians wanted to feel they could better manage costs by allocating risk to a third party, and at the time there was a sense that could work. But governments failed to recognize that you have to think about the private sector in terms of monopoly and competition dynamics. Where you want to use the private sector is for commodity services that can be procured competitively, because many providers can bid. What you want to keep in the public sector is monopoly expertise — which is harder to identify, and which you want to endure so it can learn over time. We broke that model.

We also uploaded responsibility for infrastructure to Metrolinx, which is also the owner and operator of GO bus and rail. My understanding is that Ontario would now be inadmissible to the EU, because we have an infrastructure builder that is both the operator and the builder. And we’ve seen, with arrangements like Deutsche Bahn on GO electrification, that it doesn’t work. So I’d reform Metrolinx, including separating GO operations from the infrastructure-development side.

AM: To put my cards on the table, Eric: I was in the Government of Ontario when the GTTA, as it was then called, was founded, and later when it merged with GO Transit. It’s not my world anymore, but I was there, and I’d say it never could have worked to combine a long-range planning function with an operator. GO Transit are operators; they had their own planning department, and they didn’t want to think about what was happening in other areas. And with the Deutsche Bahn situation, it’s clear they think running a diesel hub-and-spoke service for the morning and evening peaks out of Union Station is a perfectly fine mission, and why are you wasting their time asking for anything else? That blunted whatever force the former GTTA could have had as a long-range planner and as a way of prioritizing project lists. So there’s a great deal of merit to what you say.

EL: The first thing is to restore the healthy function of our institutions, because we’re spending four times, on a unit-cost basis, what others spend. Line 16 in Paris — fully underground, fully automated, built for the Olympics — came in at the equivalent of about $250 million per kilometre. We’re building the Ontario Line at $1.1 billion per kilometre, and $1.7 billion once you bundle in all the operational and financing pieces. That means we build far less than we should. Until we fix that, it’ll be very hard to dig ourselves out of congestion, because we need to build rail in the GTA the way China has built it in some of its major cities — we’re so far behind, having basically stopped for 50 years, and now everyone’s congested.

So first, fix how we build, so we can build more. Then, how do you approach building more in general? Number one, we need long-term plans for what we’re building, both for interconnectivity across the province — and I’m not sure you’ve had a chance to look at my high-speed rail proposal, which we can talk about — and for Toronto, the GTHA, Hamilton, Niagara, Windsor, London, Ottawa, Kingston, and even small centres. What’s the vision we’re building toward? How much transit will we build over the next 25 years? Once you have that vision — and even if I’m going to draw some lines on a map, it ultimately needs to be owned by an independent institution making prioritization decisions — you set up a manufacturing process to build it out. So instead of a politician like me cutting a ribbon at every announcement, it’s: our budget allocates $10 billion a year for rail transit expansion in Ontario, every year, in perpetuity, so we can build out the plan. That’s not a glamorous announcement, but it will get us far more transit if we think like a process.

AM: It’s absolutely true. The lesson from Alon Levy is that we need more state capacity — fewer consultants managing consultants. I’ll say that I’ve also been a consultant in that world, and I’ve seen the inefficiency that makes you shake your head. This isn’t a system anyone would have designed or chosen; it’s one we’ve fallen into. But let’s talk about rail.

Rail: Speed, but Also Coverage

AM: In some circles I’m the most hated man in Canada, because I’ve expressed strong skepticism about Project Alto — high-speed rail from Toronto to Quebec City, by way of Trois-Rivières, Montreal, Ottawa, and, God save us, Peterborough. One reason I think that project is ill-founded is that, to have strong high-speed rail between major centres, you need strong regional rail feeding those hubs; otherwise you’re just replicating, at great expense, the air travel we already have. So I was intrigued to read your proposal, because you seem to be proposing that Ontario, on the provincial side, build out that regional rail network — not just commuter rail into Union Station, but something much grander. Say more about your vision for Ontario rail.

EL: I’ll plug it: if you go to ericforolp.ca/HSR, you can explore the proposal. Let me share it here so you can see it.

I put this together because our premier, Doug Ford, has proposed spending upwards of $100 billion to tunnel four extra lanes under Highway 401 — already the widest highway segment in North America, I believe. I wanted to ask: what could we build with that kind of money if we put it into high-speed rail and made reasonable cost assumptions? So here’s an overview — the travel times you’d expect between destinations, and the cost assumptions for stations and for each segment. An expensive segment like Pearson to Toronto runs $170 million per kilometre, because it’s either viaduct or, in places, underground; over flat land in southwestern Ontario, it’s closer to $75 million. For reference, Project Alto assumes $60–90 million per kilometre, at least in its public announcements. You’ll also see the speed assumptions — a top speed of 320 to 350 kilometres an hour, which again aligns with Alto. The assumptions are all in the “why” section, along with the station costs I’d expect. Otherwise, you can explore the map. Anything shown as a dotted line isn’t included in my cost assumptions; everything else is. So for the segment coming through Peterborough to Toronto, I’ve actually added a stop at Oshawa — I’ll get to why — and I’ve assumed all the additional costs from Oshawa to Toronto and across the rest of southern Ontario.

Two things need to happen with Project Alto. First, we shouldn’t be talking only about the Quebec City–to–Toronto segment, because then we’re back to treating it as a project: we’ve hired a consortium, and that consortium now says it’ll be six years before shovels are in the ground. What we should pursue is the network we want over the next 25 years, and then get started fastest on the fastest segment. Look at how Spain built its high-speed rail: they didn’t start with Barcelona–Madrid, because it was more complex. They started with a simpler segment — Sevilla–Madrid, I believe — so they could learn and keep building toward the longer-term network. Second, you need to continue it to Windsor. I know some business cases suggest that doesn’t make sense, but over a hundred years of provincial economic development, it absolutely does.

The real value of a network like this is connecting the Greater Golden Horseshoe into one contiguous mega-region, from an economic and labour-mobility perspective. Right now, if you work in Kitchener–Waterloo, it’s an hour’s drive to Hamilton — some people do it, but it’s rare for these two centres, with about a million people around each, to participate in each other’s labour markets. With a connection, you could get between them in about 20 minutes, and that opens a huge world of opportunity. Same for Oshawa to the Pearson economic zone, the second-largest employment zone in the entire country. And the Toronto–Pearson connection matters because it links people to the airport, and might resolve some of our other Toronto debates. So the logic is: you can go from Ottawa to a tourist destination like Niagara Falls; from London, be sipping wine in Niagara-on-the-Lake in an hour and a half; live in Barrie and commute to Hamilton in reasonable time. Everyone in the region can reach far more employers, which means they can bargain for better jobs without the cost of moving — and employers can locate in Hamilton, Kitchener, or Oshawa and still attract talent from across the region. The whole prospect of building and investing in Ontario gets better.

AM: This plan appeals to me, again, because of my heterodoxy on rail. I would much rather have a good, fast, reliable connection between Toronto and Kitchener–Waterloo than to Montreal — because I already have a way to get to Montreal or Ottawa quickly: I take a plane. There’s no quick way to get from Waterloo to Toronto at 7:30 in the morning for a 9 a.m. meeting. You either drive — and you’re really rolling the dice — or you don’t go. It’s uncertain and unreliable, and there’s no alternative, because GO service doesn’t help. This would give the people of Ontario something they don’t have right now.

EL: I’ve heard the objection: doesn’t GO Regional Express Rail solve some of this? It’s not solving the same problem. High-speed rail makes the destination-to-destination speeds incredibly quick; what you want alongside it is strong local transit connected to it, so accessibility around each place is better too. Everywhere we put a major high-speed line, we should also be thinking about the local rapid-transit networks. Then it stops making sense to take the 400 down to the 403 from Barrie to Hamilton — you’d never do it, because it’ll always be faster and cheaper to take the train, then a bus, then maybe an Uber for the last mile. This unclogs so many of our roads, which is a huge problem in Ontario, and it creates incentives for investment and all the other things that make people’s lives more convenient.

I’ll make one more point: I’ve proposed an alternative to Project Alto here, too. What we want is to connect more of the province itself. The existing 401 corridor, which also carries part of the VIA line, has several smaller centres you can run regional service to. We should have the mindset that we’ll run both regional and express services on this network. Then it becomes possible to work in Ottawa and live in Kingston, because you only need to go in every two or three days. Interconnecting this region will probably see more traffic than a line from, say, Windsor to Montreal — and I don’t think that logic exists right now in how we think about these projects.

AM: My view — that regional rail matters more than intercity high-speed rail, that the one depends on the other — hasn’t been popular. But your plan is exactly what I’ve been arguing for; it’s very exciting. Let me add, since you raised it, that this is entirely complementary to GO electrification, which turns the GO system from a commuter rail into more of a “surface subway” — I don’t love the term, but it’s the one people use — with much shorter headways and more in-between stations, without increasing travel time, which allows for a lot more infill development. GO electrification is, I’m obliged to quip, off the rails: badly overdue and expensive. What’s your diagnosis of the problem, and how would you fix it?

EL: The biggest problem in Ontario is the same across almost every sector: a distinct lack of curiosity, from our government and our leaders, about the problems they’re tasked with solving. A month or two ago, both Prabmeet Sarkaria, our Minister of Transportation, and Doug Ford were asked about the tripling of transit infrastructure costs in Ontario, and it was, “Yeah — COVID and inflation.” You’ve been responsible for this for years, and you haven’t spent any time thinking about why these things don’t work? Here’s the problem: Metrolinx doesn’t have a true independent mandate. Most projects are contrived in ministry offices first, before they go to that supposedly separate institution. When you don’t have a mandate for institutional independence to actually make decisions, you get a lot of indecision — what I call decision-based evidence-making. And that ends up as squandered cost and time. So there has to be political will and pressure to make decisions, and to push decision-making down to independent institutions so they can move faster.

AM: I have to be circumspect, so I won’t go into detail, but from someone who was on the inside: your diagnosis is correct.

EL: One of the funny things about becoming an advocate — first with More Neighbours Toronto, and then chairing Build Toronto, the growth-oriented arm of the Build Canada movement here — is that people who are part of these systems come forward. I’ve talked to consultants and public servants. Even the consultants say, “People blame us for the costs, but we’d rather be doing twice as much; half of what we do is bureaucratic compliance nonsense, and we don’t get to do the things we want to focus on.” With More Neighbours, people would come to me from the Ministry of Municipal Affairs and Housing, or from the City of Toronto: “Can you advocate for this? It drives me nuts, but I can’t put my name to it.” I see my campaign as a platform for everyone who sees the dysfunction and knows the solutions, but who hasn’t seen anyone willing to spend the political capital to make the change. I’m running to do exactly that.

AM: So GO electrification is part of a root-and-branch reform of Metrolinx.

Road Pricing

AM: Let’s move from transit to another matter: road pricing. I’m on record calling it the number one policy no one wants to implement but everyone loves once it’s in effect. I avoid “congestion pricing”; I don’t even like “decongestion pricing”; I prefer “road pricing.” What’s your view?

EL: When I chaired Build Toronto, we published a memo on congestion pricing. For a while I thought I might avoid going on the record in support of congestion pricing. Then I realized the cat was out of the bag and I’d be attacked with it anyway, so I might as well defend a good idea. What we should focus on is the outcome people want: to be able to drive places reliably. If you brought in a pricing regime that still left people stuck in traffic, you’d get a lot of anger. But done properly, you won’t get all the traffic. So I’d employ congestion pricing in the GTHA, on our highways, to the extent needed to maintain a minimum speed of 50 kilometres an hour. That makes the highways their highest and best use at the times people need them. I recognize there are people who rely on driving for their jobs and their work, and lots of lower-income Ontarians who don’t have much choice but to drive — and there are things we can do for them. But what gets missed is that people don’t just value their money; they value their time, and we put no priority on that. A business paying a trucker $30 to $50 an hour, who’s going to spend an extra hour crossing the GTA, would have needed to pay maybe $20 to get there twice as fast. The economics work for those users too: they get to do more, move more.

Everywhere congestion pricing has been tried, it has worked, and everywhere it’s been tried, people have been loath to take it away. There’s a challenge here because of how people feel about the 407. The price shock on the 407 has made a lot of people angry, because it’s become a privileged highway. But here’s what people don’t appreciate: if we bring in congestion pricing that’s much lower than the 407 on our other highways, the 407 won’t be able to charge its steep prices to lure people off the rest of the network — so even the 407 will be forced to compete and get more competitive. What we should also learn from the 407 is that there’s private demand to own and operate highways. So for projects like the Bradford Bypass or the 413 — which have attracted a lot of controversy about whether they’re worth the government spending money on — I think the province should do the pre-permitting and set the design standards, but if the CPP or a pension fund wants to own and build a competitor to the 407, I’d love nothing more than for them to have the right to do that.

AM: I’ve written about this too, and I’m entirely in favour of managed lanes of the sort you’re describing. You just must build into the contract what you said: that the purpose is to set rates as low as possible while keeping the highway moving. If it’s just revenue collection, it leads to perverse incentives. But if the goal is to keep the lanes moving — you didn’t say it, but I assume this charge would be dynamic. At 3 a.m. on a Monday it’s low or zero, because there’s no demand; at 3 p.m. on a Thursday, as rush hour begins, it’s quite different. It reflects local conditions.

EL: Yes. The price should only reflect what’s required to keep the road moving at a minimum of 50 kilometres an hour. That’s it. People ask whether you’d use the money to reinvest in transit — yes, broadly, as part of the pool, but the goal isn’t to generate revenue for transit. The goal is mobility: making sure people can rely on the speed of the highway network.

AM: It’s not a revenue centre; it’s a transport system that needs to be managed to be most efficient as a transport system. We’re all technocratic wonks here, so we’re 100% on board with road pricing as a tool to move people and goods most efficiently.

Driving Automation

AM: Let’s talk about automation — probably the topic my readers are most interested in. We’ve flirted with automated vehicles in Toronto. We’ve got Gatik, quietly running automated trucks for Loblaw in parts of the city. We’ve got Waabi, which isn’t really doing anything here but was founded here, with big plans for Texas and elsewhere. Magna ran a pilot that was embarrassing and didn’t succeed. We had delivery robots briefly in the Distillery District before we kicked them out — it’s never been clear why, other than that they were different from the status quo and therefore mistrusted. But you lived in San Francisco while Waymo was building up, so you have a completely different perspective. What’s your take on automated vehicles, and what role would you like them to play in Ontario’s mobility system?

EL: Let me take a step back. With generalist, autonomous robotics — not just vehicles; I’ll use “robotics” — it’s almost like 1895: we’re seeing the combustion engine at the World’s Fair, but no one thinks they’re selling their horse and buggy any time soon. By 1915 there’s a mass trend toward the automobile. That’s where we are with robotics generally. And I don’t think there’s a jurisdiction with more of a right to win in this space than Ontario over the next 30 to 50 years. If we operate from fear, we’ll miss an enormous opportunity. Why? We have five or six factors in our favour.

First, we genuinely have a major centre of AI in this province. A decade ago, on the Deloitte Fast 500 fastest-growing companies in North America, Canada had about 10%, matching our share of the population. This past year we had 23%, and over 15% of the total were in Ontario — because the sector is here.

Second, we have a financial capital that augments it; New York and San Francisco can claim that too, but we have other things they don’t.

We have a resource supply chain in Northern Ontario — critical minerals and more — that feeds the physical supply chain for automotive, machinery, and mechanical engineering.

We have an automotive industry far larger than almost any competitor’s.

And we have a clean electricity grid; if we get electricity, state capacity, and industrial policy right, it could be the most competitive energy sector in North America by far.

All of this means that if we understand what it takes to produce robotic systems — vehicles and machines — for export, Ontario could be the Western leader. And we have maybe five years to capture the opportunity.

So Ontario needs to change how it permits the use of autonomous machines — vehicles, robotics; heck, I think it would be charming to have park robots that maintained our public spaces better. We need to be deliberate about permitting the ones already operating, as most of the world does, and we should be publicly clear that we’re willing to procure generalist robotics for other uses in our society. We need to move our regulatory system from “no, with exceptions” to “yes, with exceptions.” That’s the grand goal of how I view robotics, in vehicles and everywhere else.

AM: Recently, Mayor Chow of Toronto, her press secretary remarked that Waymo is only welcome in the city to the extent it won’t contribute to Uber drivers losing their jobs. So the attitude is guilty until proven innocent: this technology is dangerous, and until we can defang it of any threat to anyone, it’s not welcome. To me this is a quintessentially Canadian attitude: we prefer not to take risks, not to do anything that could, as Eli Dourado likes to say, make anyone uncomfortable or cost anyone a job. How do you challenge that broader fear of the future that seems so common here?

EL: If we meet the future with too much fear, we’ll never realize the opportunities it offers, or the jobs it could create. Whenever I hear this, I remind people that in 1850, 95% of us were farmers. Do you want to go back and work the fields? No. We now have a far greater diversity of more rewarding, higher-value, higher-productivity jobs, because we freed ourselves from low-value labour. That didn’t mean we ran out of food; it meant we got better at producing it with less human input, so we can consume more, and our material well-being goes up. So when we say we can’t say yes to Waymo, what that means is that fewer people can get around the city, because Uber has to pay its drivers to drive. With autonomous vehicles, the cost of mobility comes down a lot — which means more choice, more commerce, all the things that add to our lives.

In economics there’s a great example from the semiconductor industry: the Jevons Paradox. In the 1990s, as the cost of manufacturing semiconductors fell dramatically, there was a panic that everyone would eat each other’s lunch and demand would run out. But as the cost of compute fell, the demand for compute rose even faster — and the result was more jobs and more economic activity. When we have this mindset of protecting the past, we miss the future, and we miss how lives and material well-being actually improve. It’s a small-minded, here-and-now approach. Canada wasn’t always like this. We used to believe in progress, in development, in the future. Now we believe in putting up every barrier we can so that nobody is upset by change. That has to change.

AM: I talk a lot to American audiences, and they ask, “What about the people who lose their jobs?” And I want to say: that’s why you need a strong social safety net, so that a person’s worth, dignity, security, and future aren’t bound up in a particular job, and they can transition. Then I remember I’m talking to Americans, and I bite my tongue. But in Canada we have a strong social safety net. So — I won’t put words in your mouth — I believe there’s enough prosperity to be gained that we can tax the winners to make the losers whole, and that it’s a better deal than trying to keep the future out. If you try to protect what you have, you lose it; if you try to build something more, you gain even more besides, especially for those left behind.

EL: What people often don’t appreciate — and I’m a true liberal; I believe deeply in competition in a highly entrepreneurial economy, so that you generate wealth you can tax fairly to provide a level of human welfare befitting an advanced society — is why competition matters here. In uncompetitive markets, the incremental value of the investment and innovation you’d need to hire someone for isn’t as great, because you can bet your competitors won’t make the same investment. So when capacity opens up and you can lower your costs with AI, you don’t need to repurpose the people you had. But in competitive sectors, the extra value you get by automating a less valuable process means you can spend it where human labour creates the next increment of value, ahead of your competitors. So if you want to avoid mass layoffs and turmoil from AI, the first thing you need is a competitive economy that requires labour to take advantage of these benefits and get ahead. That means almost everything we produce in Ontario — a good or a service — gets better for the same cost, without killing jobs. That has to be understood, and I don’t think it’s appreciated enough.

Rural Areas, Remote Areas, and the North

AM: You’re running for Premier of Ontario — not of Toronto, not of the Golden Horseshoe. It’s easy to talk about mobility in the context of the Greater Golden Horseshoe, or even southern Ontario. But what’s your mobility vision for Northern Ontario? You’ve spoken about the Ring of Fire and critical minerals — how are Northern Ontarians going to get around in the future, if you have your way?

EL: A couple of things. Northern and rural Ontario never really recovered robust transit service after Greyhound shut down and subsidies for rural bus operations declined. In the long term, my high-speed rail network — connecting places like Kitchener, and building hubs like London and Windsor — would let us better serve the regions around them, and create more demand from the rest of the country and Ontario to come visit our beautiful lakefront and tourist towns. Then there’s the legacy rail network, currently owned by CN and CP. I think one of the greatest crimes in our history was selling off the land under those corridors, which has limited our ability to decide what public uses they serve. We’ve just started restoring the Northlander service to Timmins. I’d like us to look at running rail through Northern Ontario — say from North Bay to Sudbury, connected even to Thunder Bay. It wouldn’t be fast initially, but there are overnight and daytime services some people would certainly take. People don’t appreciate how many rail lines still exist to serve the mining industry up north. So there’s an opportunity to run service networks to these places — as long as we figure out what happens once you arrive locally. For some of these smaller Northern centres, it’s also about helping them diversify out of the boom-and-bust cycle and attract more kinds of people who want to live and work there, and connectivity matters for that.

Here’s the controversial part. We need to be deliberate about identifying the corridors we want to be public, or at least to have public priority on, that CN and CP own today. To get them to the table, we’ll need to be much bolder. I’ve worked in M&A for years, and sometimes you have to put a bold line on the table and recognize that you hold more cards than you think. So if CN and CP won’t come to the table on amicable use and prioritization — with consistent expectations and standards — for the passenger services I’d like to restore, then we’ll use, or threaten to use, the power of eminent domain. They’ll have the choice: an amicable agreement where they keep ownership, or potentially lose it entirely and go figure out with their investors what matters to them. Unless we’re willing to go there, they have no reason to work with us. So I’m willing to go quite far to make sure these corridors — which are ultimately a public good for trade — can do what our outcomes require.

AM: I’ve worked in a small way with the Canadian Class I railways, CN and CPKC — Canadian Pacific Kansas City, or whatever they’ve rebranded themselves to. Their attitude is, “Oh, your country was founded in 1867? We’re older than that. Back off, punk.” So you’ll need to bring a similar swagger to those negotiations to succeed. And there’s a lot to what you say. As I’ve written before, you really can’t run freight and passenger rail on the same corridor; they’re at odds. A central problem of mobility is that different uses on the same infrastructure always creates friction. There are ways to resolve it, but the easiest is different uses on different infrastructure. There aren’t many corridors where you can run passenger rail on abandoned rights-of-way; the first-best solution is to acquire the corridor, get it up to a higher-speed standard, and run it.

EL: For Northern Ontario, I don’t have all the answers about the viability of sharing the freight corridors. It’s not the ideal long-term solution, but we want the right to build on them, so that where we need separated sections to manage traffic, we can. These are long distances, and rebuilding everything wouldn’t be viable at the cost, so sometimes you accept the trade-offs. If we value keeping the North connected, this is one way to do it, alongside additional passenger service.

One more thing: our Northern highways are quite dangerous, because most are winding, with one lane in each direction. There are about 1,700 kilometres of the Trans-Canada like that, and you see dramatic numbers of deaths in winter, and closures that last a long time, with a lot of freight on the corridor. We’ve debated twinning the entire corridor for a long time, which is expensive, and there’s merit in it. But the first thing is to make it a national goal — a long-term program — and to recognize that on some segments, other options make sense, like “two-plus-one” designs with alternating passing lanes and some separation, so winter driving is far less dangerous. Funny enough, even though that’s only one less lane, it costs about five times less. So you can deliver better connectivity and safer driving for Northern Ontario faster and far more cheaply than going for perfect. We need to work with the federal government on that.

Energy and Nuclear

AM: Before we wrap up, I can’t resist throwing you one more question. Don’t give me the full pitch, but what’s the short version of your vision for Ontario’s energy economy?

EL: We should be producing — and consuming — the most electricity per capita anywhere in the world. The way to get there is to think about energy development as a system too. I’m very inspired by how the French built their nuclear advantage: they set nuclear incentives, identified plenty of future sites, did the permitting and environmental review, chose one reactor design, and copied and pasted it to bring down the capital cost. I’d have the province take responsibility for the capital cost of baseload power, which should be nuclear and hydro, and let the private sector handle variable demand — renewables and battery storage, which have a pricing mechanism built in. I’d bring the permitting for all of this up to the provincial level. Right now, to permit a battery-storage site you go through the municipal process, and everyone reinvents the wheel. I want one provincial system for rapid permitting, with pre-identified sites, so the private sector has a clear signal of where it can move, and quickly — which also reduces risk. That’s the generation side.

Then there’s consumption. We spend too much time telling people to save energy and not enough telling them to consume more. In a city — Ottawa, where I am today, or Toronto, where I live, or many others — about 90% of emissions come from heating buildings and moving people and goods. The alternatives are electric heating and cooling, and electric mobility, and both need a lot more electricity. If you own a home built in the 1980s, you might have only a 100-amp connection. Say you want an electric vehicle, a heat pump instead of your furnace, and to convert it into a multiplex — you’ll likely need a 400-amp connection. If the transformer on your street isn’t upgraded, the utility says, “You’re making us do this upgrade; give us $100,000 so we can provide that power,” and your neighbours won’t have to pay for the incremental upgrade — they’ll just apply and pay the $5,000–10,000 for their own increased connection. I’d like a clear mechanism to amortize those infrastructure upgrades over time through higher consumption, so our utilities have a clear incentive: when they upgrade a neighbourhood, they tell people, “Your neighbourhood has been upgraded — and here’s how you can consume more electricity. You’re ready, and here’s how.” We should be conditioning people to think about increasing consumption, not the other way around.

The last piece is managing the transmission infrastructure itself. If you’ve followed Ontario politics, the energy sector has talked about the “smart grid” for as long as I’ve been alive — and it’s still not that smart. That means we use a lot of grid infrastructure at very low utilization, because we don’t know its overall health. Going forward, the Ontario Energy Board needs a mandate to put smart monitoring on all of it, so we can move a transformer from, say, 30% capacity to 60%. Then we’ll know where the points of failure are and where the priorities for upgrades are, and we can sweat the assets we already have, which brings down the cost of what we’ve already built. There are a lot of components to electricity, but it all matters, because electricity will be the most important economic and environmental input of the future by far — and it’s an area where Ontario has a tremendous potential comparative advantage. We can’t miss the boat on getting it right.

In Conclusion

AM: A future of abundant electricity, abundant mobility, and abundant housing — I’m all for it. Our time has to come to a close, so let me throw you a more fanciful question. Say you somehow become premier tomorrow, and you get to do one mobility or transport thing in your first year. What is it? To give you time to think, I’ll tell you mine: I’d come up with some neutral way to classify what a higher-order transit system is, and then classify every higher-order transit stop, and then say that if you’re constructing a building such that the front door is 300 metres or less from an access point to that station, there are no more height limits — by fiat of the province. Let the market decide how much housing there should be next to a higher-order transit stop. Admittedly fanciful, but what’s yours?

EL: It’s funny, because you mentioned land use — and if it weren’t transport-specific, that would probably be my answer too. But for me it’s not glamorous: it’s the institutional reform to change how we build. If you get that right, and can build at globally competitive cost and to higher standards, it doesn’t much matter what you decide to build next. If you don’t fix that fundamental problem, nothing else matters. So I want the institutional reform. Get how we build right, and “what we build” just means building more.

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AM: In other words — abundance. Building abundantly. That’s an exit line if ever I heard one. Eric Lombardi, thank you very much for your time today.

EL: Thank you. And for everyone listening and reading: stay tuned to my campaign. If you’re in Ontario, sign up as a member of the Ontario Liberal Party — it’s free, and you can vote in November. And when the campaign launches, if you’re open to it, consider a donation, because what I’m doing here is challenging, and it isn’t free.

Thank you so much for your time, Andrew. It was a pleasure.

Long-time readers will note that Changing Lanes usually publishes longform work on Tuesdays and Off-Ramps on Thursdays, but this week we’re switching it up. I am confident you will find Thursday’s piece exciting and interesting, but to accommodate its subject, I am holding off on it for two days. When you read it, you will understand why.

Hard Fork revisits Interesting Times

Earlier this year I appeared on the New York Times podcast “Interesting Times with Ross Douthat” to discuss the state of driving automation in 2026 and where the field is going. I’m flattered that the team at Hard Fork, the NYT’s biweekly tech podcast, liked that conversation so much that they rebroadcast it under their own banner.

If you’ve already listened to my appearance with Ross, this won’t be new, but on the off chance you missed it, please enjoy it now, in a new format.

The Hub: Toronto Gets It Wrong, Again, This Time on Waymo

I wrote in The Hub yesterday on Toronto’s double standard on Waymo: the city is willing to let robotaxis in, but—as per the mayor’s press secretary—only if the firm proves that no jobs will be lost, no jobs will pay less wages than they do now, and no jobs become more precarious.

That’s a ridiculous standard to hold, as applying it consistently would mean that any innovation affecting any labour market would be subject to a veto by the workers it displaces.

For more, read the whole thing.

Investment Wars: Planning and Investing for an Automated World

On the most recent episode of the Investment Wars podcast, I joined host Joe Halpern to discuss a key problem for capital allocators: in a world where automation is clearly going to transform how we move people and goods, how should planners and investors prepare for change? How should they hedge against it? And what are some ways that air, rail, marine, and truck travel are likely to improve in future?

This was a good talk, and I hope that you enjoy it. It is available on Spotify, Apple Podcasts, and YouTube.

Radio New Zealand: How New Zealand should think about driving automation

I was pleased to appear on Radio New Zealand on the drivetime programme Afternoons with Jesse Mulligan to discuss how, specifically, New Zealand’s regulators and citizens should think about driving automation; the distinction between Tesla and Waymo; why Wellington and Christchurch are going to benefit from the technology first; and other matters.

Driving automation is a global technology, and it’s useful to think about how it will apply differently in places that aren’t North America or China, so I was grateful to Jesse for the chance to speak with him about how New Zealand specifically should prepare.

This went out over terrestrial radio, but a recording of our interview is available here.

Upcoming Events at Changing Lanes

Finally, two upcoming items.

Firstly, our next livestream! On Wednesday, 24 June at 1200h ET, my guest will be the foremost American authority on regulating automated driving: Professor Bryant Walker Smith of the University of South Carolina. Smith helped develop the SAE’s “five levels” of driving-automation taxonomy, and earlier this year he testified to Congress on how the United States should regulate self-driving. Subscribers are notified when we go live; you can also sign up here.

Second, our upcoming price change! The subscription rate for Changing Lanes goes up next week on Tuesday, 16 June, rising from the current rate of US$10/month or US$100/year to US$13/130. This means that now is the best time to change your subscription from free or monthly to annual, since switching now locks in a full year of content at the best possible rate. It’s as easy as clicking this button:

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Firstly: this Wednesday, 24 June at 1200h EST, you are invited to attend the second Changing Lanes livestream! My guest this time will be the United States’ foremost authority on regulating automated driving: Professor Bryant Walker Smith of the University of South Carolina. Smith contributed to the development of the SAE’s famous ‘five levels’ of driving automation taxonomy, and earlier this year testified to Congress about how to regulate self-driving in the US. Subscribers will be notified when we go live, but you may also sign up here.

Secondly: a reminder that in two weeks—specifically, Tuesday, 16 June—the price of a subscription will go up. The current rate of US$10/month or US$100/year ends; from that date, new subscriptions will be US$13/month or US$130/year. If you want to lock in a year of access to subscriber-only content, the time to do so is now, since annual subscriptions taken today get it at today’s lower rate.

In 2021, distraction was a factor in 29% of Canada’s road deaths, up from 19% at the turn of the century. The US is about the same, once its figures are corrected for under-coding.1 The behaviour is climbing on both sides of the border.

In response, authorities are taking action. This week, on 5 June 2026, Pennsylvania’s ‘Paul Miller’s Law’ takes effect: a driver caught with a phone in hand faces, on first conviction, a fine… of $50.

Paul Miller’s Law is the newest of the handheld bans on the books in every Canadian province and 33 US states. This regime has been spreading steadily since 2007, but the problem it aims to combat is getting worse, not better.

This mild and tremulous response is vexing. We know that distracted driving kills, and we know it is on the rise. The situation calls for decisive action, but we should be thoughtful about what kind of action. Changing Lanes is a techno-optimist newsletter: if there’s a problem, we don’t expect to fix it by hoping for a change in human nature. Instead, we expect to fix it with structural change. Given this, the token fines and thin enforcement are galling. But what is more contemptible is that a structural fix already exists—one that requires neither criminal nor civil penalties, that doesn’t require us to punish anyone, that is mandated on new cars across the European Union—and that we have declined to require it.

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In other words, we have decided to tolerate the deaths caused by distracted driving because fixing it would be inconvenient.

Why Drunk Driving Was Solvable…

To start to understand the matter, it’s helpful to begin by considering a parallel problem: drunk driving.

Between 1980 and 1997, US drunk-driving fatalities fell from around 21,000 a year to around 17,000. That’s a substantial decline—19 percent—and strong evidence that, if we resolve to, we can make progress on reducing road deaths stemming from a particular cause.

The drop in drunk-driving deaths was the product of a bundled series of policies. Specifically, we set per-se blood-alcohol thresholds; set minimum legal drinking ages; established zero-tolerance laws for drunken drivers under 21; and permitted the police to revoke licences at the roadside, independent of the courts.2

Enforcement was not the whole story, because drunk driving also lost a long cultural argument: Mothers Against Drunk Driving made it shameful in a way distracted driving still is not. So why has no comparable stigma attached to the phone? It’s partly because nearly every driver offends in this way, at least some of the time, and a near-universal act is hard to shame. It’s also because it cannot be reliably seen: a phone held at lap level is invisible outside of the vehicle. Even so, a stigma campaign is worth attempting; I’ve urged such approaches to solve other problems, and Families for Safe Streets is trying just such a move.3 I doubt it will be enough on its own. We will need enforcement as well.

Notice that enforcing rules against drunk driving depended on a single question: can police establish that a driver they have pulled over is over the limit? If they can, the anti-drunk-driving policy suite is sound. But if they can’t, blood-alcohol thresholds, minimum drinking ages, zero-tolerance regimes, and license revocation are useless.

Thankfully, the police do have a way to do this: the Breathalyzer, invented in 1954. Courtesy of the Breathalyzer, police can quickly and cheaply test a driver’s blood-alcohol level at the roadside, enabling the rest of the policy bundle to bite.

…But Distracted Driving Isn’t

So is there a Breathalyzer for distracted driving, a simple technology that can quickly and definitively establish a driver is not paying attention behind the wheel?

Right away, we can see that it’s a hard problem. Intoxication is a state; it persists even after a driver pulls the car over and turns off the engine. Distracted driving is an activity.

As such, it is hard to detect, because it can stop at any time. As soon as a police officer puts on their lights and sirens, the driver is no longer distracted. So the crime must be established by the traces it leaves behind, or by some record taken at the moment it is happening.

Establishing it by its traces is legally challenging. The place to look is on the distracting device itself, i.e., the driver’s phone, and we have the means to do so. The ‘textalyzer’—a device that reads recent phone activity post-crash—has been proposed in several US states and adopted in none, stalled by privacy and Fourth Amendment objections. The grounds for this were established in State v. Dunbar (Connecticut, 2016), which says the police cannot interfere with someone’s phone absent proof beyond a reasonable doubt that the driver was engaged in a call. Simply having a phone in hand is not enough.

I am dubious about the legal doctrine here; it seems to me that a policy may establish, as a reasonable standard, that holding one’s phone while driving is illegitimate, which would be grounds for a ‘search’ of that phone to establish its use. I will grant that permission for state inspection of our digital lives and devices must meet a high standard, given the privacy implications, but we seem to have set the bar so high that honouring it has given us a basically-nonfunctioning enforcement regime.

"Distracted driving" by Mike Skoropad is licensed under Creative Commons. Image courtesy of utires.com.

Set the matter aside. If we cannot establish distracted driving after the fact, we must instead establish it at the time of occurrence. The simplest way to do that would be to use some kind of device that can detect it in real time and make an immediate record.

We have such devices: cameras.

New South Wales (NSW) in Australia has operated AI-powered mobile-phone detection cameras since 2019. (Since from the ground one cannot see whether a driver has a phone in their lap, they are mounted to elevated positions near the roadway.) As a consequence, detected-illegal-use there fell from ‘one vehicle in 82’ to ‘one vehicle in 597’ in under four years, a reduction of approximately 86 percent.

Findings like these reinforce my conviction, stated more than once, that public surveillance offers great advantages that we should pursue.

But set this aside as well; I am in the minority on this point. Most voters deplore the idea of cameras being ubiquitous in public spaces, and a single jurisdiction’s results are not yet enough to lean on, though NSW road fatalities caused specifically by distraction have continued to fall.

It follows, then, that if we can’t put cameras on the roadside, we must instead…

Read more

• Bern’s history in the transportation field

• The pick-up-and-drop-off problem and why cities have to solve it

• My doubts about Bern’s view of the problem, and his responses

• Questions from the audience

I hope you enjoy it!

Get more from Andrew Miller in the Substack app

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Welcome, dear reader, to Off-Ramps, that occasional miscellany of intelligence, carefully gathered in these pages of Changing Lanes, for the discerning subscriber. Upon this occasion I beg leave to lay before you three matters of some urgency.

1. Mr. Bern Grush, in Person, at Noontide

Upon this day, at the hour of noon (by Eastern reckoning), I shall have the honour of opening the Changing Lanes Substack Live series of colloquies with Mr. Bern Grush.

Mr. Grush is a co-author of my volume The End of Driving. We will discourse upon the subject of the future of urban mobility, as well as the new commercial enterprise he has founded in pursuit of that future. I give fair warning that Mr. Grush and I are not in perfect accord upon this subject, and we shall probe our disagreements with some vigour. I expect it will prove a spirited exchange.

Pray make a note in your diary and join us, here. The discussion shall be open, and I shall be entertaining questions; and so I do beg you to bring your own.

2. The Roots of Progress Fellowship Closes upon the 1st of June 2026

To any reader who writes, or who aspires to do so, this notice is deserving of your attention, all the more so given how little time now remains.

The Roots of Progress 2026 Blog-Building Intensive (BBI) Fellowship is a course of ten weeks — part-time, conducted at a distance, and free of any charge whatsoever. It pairs a programme of instruction in the long-form explanatory essay with the benefit of professional editing and counsel. Besides these, it offers its members a fellowship of some thirty kindred spirits, not to mention that the Fellows shall be brought into the company of the foremost thinkers in the study of progress and the policy of abundance.

This intake is the fourth cohort of the BBI. I myself was a member of the second, and the experience has altered the course of my life. The BBI furnished me with the implements, the camaraderie, the encouragement, and the confidence I required to set down my thoughts in public. Should these be the things you yourself require, that you might advocate for a better world, then by all means you ought to apply.

The final day for application is the 1st of June; pray, then, apply here, and without delay.

3. A Word Concerning the Subscription

Changing Lanes owes its existence to the fact that I take pleasure in writing as an independent man, unbeholden to the editorial line of any single publication. Yet it must flourish sustainably, given the cost in foregone labour that its writing exacts. And so, by way of reminder, upon Tuesday, the 16th of June, the price of a subscription shall be raised.

The present rate of ten American dollars per month, or one hundred per annum, will be discontinued; from that date, new subscriptions shall be thirteen dollars per month, or one hundred and thirty per annum. Those presently subscribing on an annual basis shall retain their current rate until the date of renewal, whilst monthly subscribers shall be moved to the new rate upon the first occasion of their being billed (subsequent to the sixteenth of June).

The implication is that the prudent reader who has been contemplating subscription would do well to act now, for annual subscriptions taken at today's rate shall be secured for a full twelvemonth.

Before we get to that, though, two reminders:

Firstly: this Thursday, 28 May at 1200h EST, you are invited to attend the first Changing Lanes livestream! My first guest will be Bern Grush, a co-author of my book The End of Driving, on the future of urban mobility, and the start-up he’s founded to build that future. Fair warning: Bern and I have some disagreements on this subject, which we will probe. I think it will be a fun conversation! Subscribers will be notified when we go live, but you may also sign up here.

Secondly: a reminder that in three weeks—specifically, Tuesday, 16 June—the price of a subscription will go up. The current rate of US$10/month or US$100/year ends; from that date, new subscriptions will be US$13/month or US$130/year. Existing annual subscribers keep their current rate until renewal, while monthly subscribers move to the new rate on the first billing cycle after 16 June. What that means is, if you’ve been thinking about subscribing, now’s the time, since annual subscriptions taken at today’s rate will be locked in for a full year.

Alto, Canada’s putative high-speed rail (HSR) project, has a published business case. It also has consultation FAQs (which cover 50 topics, including winter resilience and Indigenous collaboration), a Transport Canada environmental and economic assessment, and published testimony from its CEO to the Senate of Canada.

Nowhere in any of these documents is any treatment of automated vehicles (AVs) as a demand risk to the project. There is no spirited engagement with AVs; nor a hedged acknowledgment of them; not even a dismissal. There is no treatment of AVs at all.

That’s remarkable, because Alto is an infrastructure project, projected to cost $60–$90 billion CAD. Bear in mind that driverless freeway service and driverless intercity trucking are both already in commercial operation, meaning that it’s reasonable to expect highway-and-urban AV, privately owned and/or available for hire, by 2035, before Alto’s first segment is scheduled to carry a fare-paying passenger.

In other words, Canada seems poised to build a massive infrastructure project through the heart of Quebec and Ontario, at massive cost, even though its value proposition may be superseded before the first train runs.

It has happened before. Consider the St. Lawrence Seaway.

The Seaway opened in 1959, a joint Canadian and American project that gave ocean-going vessels the ability to travel 3,700 kilometres inland, as far as Duluth and Thunder Bay. It was one of the great engineering achievements of the postwar era.

That may sound like success. It is, but unfortunately a heavily qualified one. The Seaway reached its peak in 1977, and today carries two-thirds of the cargo it did then, fifty years ago. It ships bulk commodities, mostly grain and ore, and essentially no container traffic.

Alto is on course to become the Seaway of our era: a project that construes a problem, and solves it at immense cost, even as the world changes such that the problem recedes in importance. Canada’s embrace of it suggests that, once again, the country will skate to where the puck has been and ignore where it is going.

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Why the Seaway Underperformed

The St. Lawrence Seaway was a genuine achievement.

Grlakes lawrence map-blank.svg, CC BY-SA 4.0, via Wikimedia Commons

The problem it was trying to solve is immediately evident upon consultation of a map. The St. Lawrence River drains the vast inland seas of the Great Lakes. The St. Lawrence narrows beyond Montreal, which was not an accident; Montreal grew up where it did precisely because that was as far as ocean-going vessels of the pre-industrial age could reach. But after 300km of intermittently tight and sloped stretches, the river widens out into Lake Ontario. It was clear from Canada’s early days that the construction of locks along the Montreal-to-Kingston segment could permit Atlantic vessels to reach Toronto; further upgrades to the Welland Canal would grant access to Detroit; and further work beyond would open up the remainder of the Great Lakes, bringing ships as far inland as Chicago, Thunder Bay, and Duluth.

Canada had urged construction since the early 1900s, but opposition from American railways and ports blocked it for decades (they didn’t want competition). The deadlock broke in the early 1950s, when post-war anxieties about iron-ore supply for the U.S. steel industry gave the project the national-security framing it needed. Enabling legislation passed in 1954; construction took just under five years, with the formal opening in June 1959. It cost about $460 million CAD, with the Canadian government paying slightly more than two-thirds; Canada spent a further $300 million enlarging the Welland Canal. The Seaway came in on time, within authorized budgets, and has been continuously operational for sixty-five years and counting.

The Seaway was a success, at first. Cargo volumes rose through the 1960s to peak at just over 57 million tonnes in 1977. Since then, it’s been in slow decline: today the Seaway moves roughly 37 million tonnes, of which three-quarters is still iron ore and grain (almost no consumer goods).¹

What happened? Why did the Seaway become only a modest success?

In a word: containerization.

The containerization revolution is well known. By shipping goods of all sorts in a standard container (eight feet wide, eight and a half tall, twenty or forty long) that could be moved en bloc from ship to railcar to warehouse, the costs—in transshipment, in security, in protection—of goods movement dropped, enabling the globalized economy we enjoy today. Containerization kicked off when the converted T-2 tanker, the Ideal-X, carried 58 thirty-five-foot containers from Newark to Houston in April 1956. Within fifteen years, the container had remade global shipping, a revolution the Seaway missed entirely; today it moves virtually no containers.

Why? For two reasons.

The first is structural. The Seaway’s locks are sized to match the existing locks on the Welland Canal. Containerization encouraged the emergence of bigger ships with deeper drafts, rated Suezmax or Panamax (the maximum size that could be accommodated by the Suez and Panama Canals). The Welland is too small, limiting competition and capacity.

But so what? Why didn’t smaller container vessels, sized to fit the Welland locks, emerge? That was because of the second reason: economics. Bulk cargo like the Seaway was built to handle, grain, ore, and coal, tolerates slow, seasonal, low-cost transit because the goods are low-value-per-tonne and inventory carrying costs are low. A shipload of iron ore can sit in transit for weeks without straining anyone’s balance sheet. But containers are not like that. Containerization collapsed the time and labour cost of port-to-port transfer. Removal of that bottleneck changed the game, creating a new market: carriage of high-value goods on tight delivery schedules in supply chains designed around just-in-time inventory. Bulk cargo shipping continued to compete on cost over distance, but containerization introduced a new higher-value market competing on speed.

The Seaway was built for the former, not the latter; shipping by the Seaway was and is slow. The full Seaway run from Duluth to Montreal runs five to seven days, with the Welland Canal alone taking roughly twelve hours to transit. Compare that to travel time from the Port of New York and New Jersey, the ‘must-call’ container hub for the U.S. Northeast. From there, a truck can reach most of the Great Lakes industrial heartland, i.e. the Seaway’s terminal point, inside twenty-four hours. (Rail can do it within forty-eight.) The Seaway’s structural disadvantage on container time-to-market is roughly an order of magnitude.2

In the decades since containerization came to dominate global shipping, the Great Lakes ports have tried to adapt the Seaway to the new world, but in vain. Sea3, sponsored by the Hamilton Port Authority, began container feeder service to Montreal and Toronto in July 2009 and was terminated within roughly a year. The Great Lakes Feeder Line began service from Halifax to Montreal and Great Lakes interior ports in July 2008 and lasted about as long. It’s notable those were both Canadian operators, eager to find alternative routes to market; no U.S. operator has attempted a Seaway container feeder service at all.

This was, and is, the Seaway’s problem: it is infrastructure built well for a paradigm that was already fading at the moment of construction. The Seaway asked “how do we move bulk cargo from inland to the sea?” just as a new question, “how do we connect North American industry to global container trade?” was about to emerge. The Seaway is a good answer to the first and no answer to the second.

Canadian Transfer, Niels Johannes, CC BY-SA 4.0, via Wikimedia Commons

And yet, I come to praise the Seaway, not to bury it. An informed observer in 1954 would not have encountered any mention of commercial container service in trade-press summaries of cargo handling. The Ideal-X did not sail until 26 April 1956, almost two years after the Seaway’s inception. The first cellular ships (i.e., purpose-built to accommodate stackable containers) were not constructed until 1968. Canada’s first container terminal opened in Halifax in 1971, twelve years after the Seaway did. In 1954, the question “will containerization replace bulk handling?” had never been asked.

Which prompts us to wonder, has Alto missed anything important about the future movement of people?

It certainly seems that it has.

Why Alto Will Underperform

Stipulate that Alto succeeds if, once in operation, its fares exceed its operating costs; we will set aside its high-eleven-figure capital cost. We’re being generous in so doing, since any reasonable cost-benefit test would not set capital costs aside; indeed the project’s own business case does not. But it gives us a reasonable definition of ‘failure’, under which the AV question is fair game: a paradigm shift that suppresses ridership is a direct threat to the operating-revenue line. This is not a stringent test. The Tokaido Shinkansen passes it; so does Paris–Lyon. Where high-speed rail is well sited, fares cover operations and then some.

Today, in 2026, Waymo runs commercial driverless freeway service across Phoenix, San Francisco, Los Angeles, and Austin. Aurora has been running fully driverless freight trucks between Dallas and Houston, a corridor roughly the length of Alto’s first segment, since April 2025, with a second corridor (Fort Worth to El Paso, six hundred miles) added in Q3. The trajectory is unambiguous: driving automation is moving from urban geofences onto highways and from fleet to private-sale offerings. But Alto’s planners have not factored it into their plans.

So let’s do it for them, and consider: what are the likely consequences of automated driving, capable of both urban and highway travel, available at scale?

Alto’s business case projects 24 million annual trips by the 2050s, rising to 43 million by the 2080s. Those numbers assume intercity travel demand in the 2040s and beyond will look roughly as it does now: trips between fixed downtown nodes, on schedules, by people choosing rail over driving or flying. We only have one independent stated-preference study of demand on Alto’s corridor, courtesy of McGill University’s TRAM Lab. It reaches the much lower figure of ~16 million riders at Year 15 of operation, rising to 22 million by Year 50. The TRAM survey of 6,738 corridor residents found that one in three would take HSR at least once a year. Lead author Ahmed El-Geneidy has called even this estimate generous: “We gave them the benefit of the doubt [that] the demand is going to be really, really increasing very much.”

The TRAM analysis is bottom-up, built from stated preference, where Alto’s is top-down, built from a modal-share assumption that rail’s share of Toronto-Montreal trips will quadruple from 10 per cent to 40 per cent. Top-down HSR modal-share forecasts have a documented optimism bias; Bent Flyvbjerg’s survey of 210 projects in fourteen countries found that ridership forecasts systematically exceed delivered ridership.

So there is a problem: TRAM runs well below Alto at both horizons—about 15 million against Alto’s 24 million around 2050, and 21 million against 43 million by the 2080s—a shortfall that widens from a third to roughly half as the forecast runs out. Even before any AV consideration enters the picture, Alto’s investment case is teetering. And then driving automation (which, importantly, is not a factor in TRAM’s analysis either) gives the pillar another blow.

Specific predictions about the future of driving automation are a fool’s errand: there are too many unknowns to say what technology and services will exist decades from now. So let’s confine ourselves to general predictions, and imagine that there will be vehicles that can complete a roughly four-hundred-kilometre trip, without a human driver, on highways and metropolitan roads, and available for hire or purchase.

We can see such an outcome emerging, on two different trajectories. The robotaxi geofence keeps expanding: Waymo’s San Francisco service area, which started in part of the city’s eastern half, now covers roughly 260 square miles including SFO and the freeways into it. Robotaxi service starts in the dense urban core and steadily expands outward, picking up highway segments along the way. In parallel, privately-owned AVs are arriving: Tesla aims to sell vehicles without steering wheels to private buyers, and other manufacturers are developing comparable offerings. Either of these on its own delivers a viable intercity competitor; both happening at once is a likelier outcome than the planning case assumes.

That competitor won’t win on speed, but speed has never been the only axis that mattered. As I have noted before, HSR itself doesn’t win on speed; “high-speed” compares to other rail, not to commercial air, which wins by a wide margin. In its markets, HSR thrives anyway, because air’s terminal-to-terminal advantage is partly absorbed by airports being twenty to forty kilometres outside city centres, security screening adding half an hour, and baggage adding more. So against commercial air, HSR loses on speed but wins on overall trip time… if downtown is where the passenger is going. Similarly, AVs lose to HSR on speed but win on access, at trip end and beginning, since they are door-to-door and on no schedule.

Recall that the Seaway lost, even though it continued to beat container shipping on cost-per-tonne, because the relevant axis of competition shifted to speed-at-hubs. Similarly, an intercity AV (whether owned or hired) shifts competition from speed to convenience: AV solves the list of frustrations a rail or air traveller is asked to tolerate. These include getting to the station, getting from the station, travelling on a schedule, carrying luggage, sharing space with strangers, going through airport security (if flying), and on and on. None of those costs are large in isolation, but together they make foregoing them attractive.

An AV will incur none of these costs. It arrives where the passenger is and leaves them where they want to go. It runs on the road network that already exists and serves every destination in the country. As such it’s attractive for the very large share of trips that neither begin nor end in the downtown core, but somewhere in the metropolitan sprawl around it. For the rail passenger whose origin and destination happen to be downtown, the rail terminal is a convenience. For everyone else, it is the first inconvenience of the trip.

Will everyone take this option? Certainly not; a trip from Toronto to Montreal by Alto will take two to three hours less than by AV, meaning that rail wins on trips that require speed (but air will continue to beat rail on that metric). Similarly, the AV trip won’t be cheap. Long intercity trips are the hardest use case for shared-fleet economics: a four-hundred-kilometre haul ties up the vehicle for hours, and may require a deadhead return, which is the hardest pill to swallow. (Private vehicles dodge the deadhead cost, but only for those who own one.) But the question is not whether everyone will take this option, but whether enough will to imperil Alto’s business case. Business-class airfares run four to six times coach, and the cabins fill up; people pay for what they value, and what they value at the long end of the travel-comfort spectrum is freedom from terminals, schedules, queues, and other passengers. AVs offer a kind of intercity convenience that no rail product can.

Let’s make a defensible estimate for mass-market intercity AV capability — that is, a commercially-available vehicle that can complete a 400-kilometre highway trip without a human driver: let’s say it arrives by 2040. That is roughly the time we might expect Alto’s first phase to open, with the Ottawa–Montreal segment expected to carry fare-paying passengers in the late 2030s at the earliest. The full Toronto–Quebec City corridor has no published completion date, and Alto’s own FAQ says each construction phase takes seven to ten years.

I can’t say that AVs will absorb Alto’s ridership; predictions are hard. But I can say that Alto’s published case does not address this question at all. California’s HSR project has its share of failures, but at least mentioned AVs and ride-hailing in its 2018 business plan. Alto, authorized in 2025–2026, with Waymo on the freeway, does not.

What Alto Owes Us

The “Seaway question” survives the optimistic scenario for Alto: even if the project appoints excellent leadership, picks the right stations, reforms its process, and reaches its own ridership projections, the question remains. Was this the right problem to solve at this scale, with this technology on the horizon, at this moment?

I am dubious. I cannot prove Alto will fail; nobody can prove a project will fail 30 years before it opens. But I can say that Alto has not done the work to prove it won’t. A country committing somewhere between $60 and $90 billion to fixed-corridor infrastructure should be able to explain why distributed AI-driven mobility doesn’t make its bet obsolete before the first train runs.

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I would love to see an Alto business case that explicitly stress-tests ridership against a 2040 Level 4 highway scenario. If the case holds even with aggressive AV adoption assumptions, my objections here lose their force. I hope that Alto’s planners engage this question seriously, and prove that I’m wrong. Until they do, here is the bet I’ll make. At TRAM Lab’s 15-million-rider scenario—itself two-thirds of Alto’s headline number—TRAM models a $1.28-billion annual operating subsidy, with the system not turning operationally profitable until Year 44. A meaningful AV haircut on TRAM’s already-conservative figure takes operating breakeven out of reach within the concession horizon. That is the specific risk Alto’s planners owe their public a serious treatment of. Until they provide one, I expect Alto to need indefinite operating support — exactly the structural pattern the Seaway settled into when Parliament wrote off its capital debt in 1977.

The Seaway opened in 1959 and almost immediately found itself in the wrong shipping era. Alto will break ground in 2029. The chance to ask whether it is being built for the right travel era is now, before paper is turned into cement.

Respect to for comments on an earlier draft of this piece.

1. Bern Grush, live, next Thursday

On Thursday, 28 May at 12:00 p.m. ET (noon Eastern), I’m opening the Changing Lanes Substack Live interview series with Bern Grush.

As you may know, Bern is one of my co-authors on the second edition of The End of Driving. He’s also the executive director of the Urban Robotics Foundation, and the lead drafter of the ISO standards that will govern how automated vehicles deal with curbs and sidewalks. He’s also the founder and CEO of a new venture, PudoCity, which will be the subject of our conversation.

I can’t speak for Bern, but I think his elevator pitch goes like this.

Most of the robotaxi debate is about the vehicle, but the hard problem is actually the curb. Once a city fills up with driverless vehicles, where will they all actually stop to pick you up and drop you off? It’s a hard problem, made harder because many of these places that have never managed their curb space well to begin with.

For my part, I agree there is a real matter of concern here, but I have questions about whether Bern’s proposed solution can hold up as a business. Come watch me ask those questions, and decide for yourself.

Set a reminder and join us live here. It’s live, the chat will be open, and I’ll be taking questions, so please bring yours!

2. The Roots of Progress fellowship deadline is 1 June 2026

If you are a writer, or an aspiring one, this item is worth your attention, given how little time remains.

The Roots of Progress 2026 Blog-Building Intensive (BBI) Fellowship is a ten-week, part-time, online, and free programme (27 July to 2 October) for writers and bloggers excited about progress. It pairs a writing course focused on long-form, explanatory essays with professional editing and feedback, plus a cohort of roughly thirty like-minded peers. Fellows will meet leading thinkers in progress studies and abundance policy, along with experts in this year’s optional deep-dive tracks: human talent and potential, and security and resilience.

This intake is for the fourth cohort of the BBI. I was a member of the second cohort, and it’s no exaggeration to say that it has changed my life. The BBI gave me the tools, the community, the support, and the confidence I needed to write in public. If these are the things you need to advocate for a better world, you should certainly apply!

If that was not enough, Fellows who complete the programme receive a free ticket to the invitation-only Progress Conference in Berkeley this October, featuring—among others—the co-CEO of Waymo, two Nobel laureates, and other luminaries (including me!). The final deadline is 1 June, so apply here soon!

3. A note on pricing

Changing Lanes exists because I like writing independently, outside any single publication’s editorial line. And I’ve been successful at it: over the past year, the number of subscribers to this newsletter has more than doubled, from 700 readers then to 1,800 today (helped along by my appearance earlier this spring on Ross Douthat’s New York Times podcast “Interesting Times”). Changing Lanes is growing!

But it needs to be sustainable too, given the opportunity cost of writing it. So, as a reminder, in four weeks—specifically, Tuesday, 16 June—the price of a subscription will go up. The current rate of US$10/month or US$100/year ends; from that date, new subscriptions will be US$13/month or US$130/year. Existing annual subscribers keep their current rate until renewal, while monthly subscribers move to the new rate on the first billing cycle after 16 June. What that means is, if you’ve been thinking about subscribing, now’s the time, especially as annual subscriptions taken at today’s rate will be locked in for a full year.

In concrete terms, paid subscribers get two things that free subscribers don’t: a paywalled issue each month, and direct engagement from me in the comments. But equally importantly, they receive my gratitude for keeping Changing Lanes alive: reader support is what keeps it going.

As a reminder, then: the price of a subscription goes up on Tuesday, 16 June, but until then, the current rate holds: US$10/month or US$100/year. If you’ve been meaning to upgrade to paid — or to switch from monthly to annual — doing it before 16 June locks in the current rate. And if you’re already a paying subscriber: nothing changes for you today. You keep your current rate through your next renewal.

4. And finally, the memes

I often post memes to Substack Notes to illustrate posts I have written, the contretemps du jour, or just random thoughts I have had. For the benefit of readers who aren’t on Substack Notes, here they are: no explanation, no context, and no apologies. Enjoy!

I’m pleased to report that last week, the Washington Post published my argument that no one likes back-to-back meetings, but that there is a simple solution to the problem: a calendar setting everyone has access to, meaning you can solve this problem with two clicks.

If that op-ed is how you found Changing Lanes, welcome! Changing Lanes is a weekly newsletter on mobility innovation, covering everything from vehicle automation and transit policy to the platform economics of Uber. Recent pieces have covered California Forever’s mobility vision; why ghost kitchens failed; the structural reasons why air travel is unpleasant; and how to think about robotaxi liability.

As for me, I’m a transportation professional active full-time in the field, and a freelance writer who, in the past six months, has published in outlets as diverse as the Wall Street Journal, the Globe and Mail, American Affairs, the New York Post, and Asterisk.

You may wonder why Changing Lanes exists, given the other opportunities I have to publish my work, and the demands on my time. The reason is that I like writing independently, outside any single publication’s editorial line. And I’ve been successful at it: over the past year, the number of subscribers to this newsletter has more than doubled, from 700 readers then to 1,800 today (helped along by my appearance earlier this spring on Ross Douthat’s New York Times podcast “Interesting Times”). Changing Lanes is growing!

But it needs to be sustainable too, given the opportunity cost of writing it. That’s why, in four weeks—specifically, Tuesday, 16 June—the price of a subscription will go up. The current rate of US$10/month or US$100/year ends; from that date, new subscriptions will be US$13/month or US$130/year. Existing annual subscribers keep their current rate until renewal, while monthly subscribers move to the new rate on the first billing cycle after 16 June. What that means is, if you’ve been thinking about subscribing, now’s the time, especially as annual subscriptions taken at today’s rate will be locked in for a full year.

In concrete terms, paid subscribers get two things that free subscribers don’t: a paywalled issue each month, and direct engagement from me in the comments. But equally importantly, they receive my gratitude for keeping Changing Lanes alive: reader support is what keeps it going.

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recently catalogued seven beliefs that cluster among low-trust, populist voters. It’s so good that I want to quote it at length.

• There are no positive-sum trades. In every exchange, someone is winning and the other person is losing. Profit is usually a sign that someone’s been harmed.

• Every trade-off is a trick. Anything harmful cannot be made up for by other unrelated positive effects. If someone tells you we need to make a trade-off, they’re hiding a much better solution where everyone’s better off and nothing bad happens.

• Big, global institutions are always way less trustworthy than small, local institutions. The real political axis is the virtuous, authentic, everyday, rooted people vs. the unrooted powerful cabals who run society.

• It’s very important that all resources be spent on your specific value system and vision of the good life. Pluralism is a trick. Other people pursuing very different values are basically always a threat, because there are no positive-sum trades.

• The world is getting irrevocably worse. Technological progress is always just a march toward something worse.

• Individual humans are magic. Any implication that things humans do can be truly replicated by machines is an attack on human dignity.

• Some form of a folk labor theory of value is true. The value of a good is determined by how much thoughtful human labor has gone into making it.

Reading this list, my immediate thought was that the same cluster shows up in opposition to driving automation.1

Masley introduces this framework to discuss popular objection to data centres, which is real and increasing everywhere, including Canada. It’s a useful exercise in helping to separate object-level from subject-level thinking, and recognizing how a great deal of opposition to data centres stems from blanket pattern-matching.

In my view, the same separation is worth doing for automated vehicles (AVs).

Where the framework travels

No positive-sum trades. This is a standard move. On this view, every Waymo ride steals work: from a cab driver, or a ride-hail driver, or the local transit system. (This image, and all subsequent ones, link out to the original.)

On this view, benefits accrue entirely to one party, harms entirely to another, with no overlap. The possibility that a cheaper, safer transport service might leave working people better off as riders, even as it displaces some of them as drivers, is ruled out by the framing.

Every trade-off is a trick. This is clearest on safety.

Waymo’s per-mile injury rates in the cities where it operates are meaningfully below human-driven baselines. The beginner-level move is to not engage with this data, arguing that safety is unproven without addressing the existence of evidence to the contrary. The impressive master-level move is to argue that robotaxis are a complex and foolish kludge, and that the obvious better move is to simply retrofit all cities such that cars are unnecessary.

Big global institutions are less trustworthy than small local ones. This one travels strongly.

The idea here is that piloting transportation technology on public streets, where it will be used, is illegitimate, because it’s big companies based far away that are doing it. It’s easy to pair with the implication that any city councillor who lets AVs operate has been captured. As with data centres, when a national or global firm like Waymo or Tesla wants to operate locally, their bigness makes them suspect, and the actual question of whether the operation is net good for the community is skipped. (I have seen this dynamic in operation up close and personally).

Pluralism is a trick. On this view, if anyone doesn’t want a robotaxi on their street, then no robotaxis should be permitted anywhere in the city at all.

It’s reasonable for a city to consider where and on what terms AVs should operate, but on this view the only question is whether they should be present, full stop. The idea that the city should accommodate the desire of consenting adults to use the service while addressing externalities that arise does not appear.

The world is getting irrevocably worse. Hello, Black Mirror:

On this view, robotaxis are a step toward a colder world: algorithms piloting machines, workers displaced, and public streets converted into a private revenue stream for tech firms that do not answer to anyone local.

On another view, the actual dystopia is the status quo of roughly 40,000 annual U.S. road deaths because of poor human driving, and hundreds of thousands more worldwide. Driving automation is the most promising solution on offer to solving that problem; but because that problem already exists, it is generally taken as a neutral baseline rather than as a catastrophe to be urgently addressed.

Individual humans are magic. I think robotaxis surface this claim even more strongly than data centres do.

This move, from ‘some rides involve genuine human contact’ to ‘human connection is the essence of what a taxi is’ is precisely what Masley is pointing at.

Folk labour theory of value. Put one way, this is just the previous objection in different words: a ride is only really worth something when a human has provided it.

Put another way, it’s an economic claim: AV firms are extracting value they haven’t earned. None of the deployed capital, the research and development, the data infrastructure, the years of testing counts as the kind of investment that legitimates a return. Real value, on this view, comes from human effort applied directly to a task, and anything else is rent. From this, the conclusion follows that AV profits should be heavily taxed and redistributed to displaced drivers, and that the appropriate posture toward an AV firm is suspicion of rent extraction rather than recognition of value creation.

This objection, and the previous one, measure the worth of a transport service by its inputs, specifically human input to operation, rather than the outputs, i.e., what the rider gets out of it. A trip provided by a person is categorically different from a trip provided by software, irrespective of the rider’s experience or cost.

While this summary has teased out the individual objections, it’s usually the case that they travel in packs. San Francisco Supervisor Jackie Fielder manages here to hit all of them at once:

What lies beneath

This framework’s value is in identifying the style of opposition, which is real and prevalent. That’s a useful contribution, but let’s respect its limits; it would be a misuse of the framework to conclude that all the objections here are without merit, merely because of the way they are articulated. Robotaxis do pose several policy difficulties that deserve serious consideration, irrespective of who points them out or how they are phrased.

Robotaxis operate in shared public space, and as such can offer physical risk to non-users. ‘Let consenting adults transact’ is not an answer here the way it is for a data centre. It’s reasonable to ask for safe operation to be demonstrated before permitting widespread rollout… but of course there is no regulator nor robotaxi firm that asserts otherwise.

It’s true that the populist view that there are no positive-sum trades is wrong on its face. If a robust robotaxi system makes travel cheaper, more trips will be taken; because travel is expensive, there are some trips people would like to take but don’t because of cost, and robotaxis would allow those trips to happen. This is induced demand at work: just as new highway lanes encourage more trips to be made, so too will cheap robotaxi networks. More trips means more people are better off.

Artist’s conception

But it won’t all be positive-sum. Human-driver ridehail companies will face direct competition from a service with a structurally-lower cost base, and transit agencies will bleed users to a cheap alternative that offers private and direct trips. There is a genuine trade-off here; some parties are going to be worse off. Waving away concern about this as folk Marxism is no way to win hearts and minds.

Similarly, induced demand bites as hard with robotaxis as it does with new highway lanes; we may expect both to generate congestion. Ironically, the solution here, road pricing, is politically difficult to deploy in most North American cities because of the very same populist hostility.

The ‘humans are magic’ claim in its strong form is silly, but a weaker version has merit. The populist version is wrong: there is no metaphysical link between a taxi driver and a patron, and only rarely a moment of profound human connection. Most customers, in practice, spend their taxi or ridehail trips scrolling their phones in silence, and it’s the bored driver who wants to make small talk (Uber has its ‘request a quiet driver’ feature for a reason).

But human operators of taxis, rideshares, and buses really do perform functions beyond piloting: answering patron questions, handling medical emergencies, and deterring antisocial behaviour. Robotaxis (and, one day, automated transit buses) will have to handle these too, through fleet response, dispatched staff, in-vehicle communications, and a redesigned operating model. The duties don’t disappear with the driver, but will instead be relocated, and a thoughtful AV policy framework will have to ensure they have been relocated competently.

Given these real policy issues, we can’t just point out a populist move and then dismiss the speaker, tempting as it may be.

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On one side, there are genuine concerns about shared public space, congestion, and the fortunes of the vulnerable (not only ridehail drivers, but everyone who depends on a flourishing public transit system) that tend to be expressed in this register. On the other, everyone gets to vote, which means that widely-articulated views must be met with argument, not sneering. Robotaxi advocates must shoulder the burden of demonstrating safe operation in shared streets; pricing the externalities that automation will amplify; and using some of the profits of the winners to reduce the pain of the losers.

We had best take this seriously, or we will spend the next decade winning the argument but losing the politics.

It consists of five questions that will take about two minutes to answer. The goal is to help me better understand you, the primary audience for Changing Lanes, and what you find most useful about the newsletter. That information will shape both what I write…

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Firstly, I’m pleased that the New York Post solicited a guest column from me on how to fix the TSA. If that whets your appetite, I go into more detail here in Changing Lanes, in “Airports Are Too Safe”.

Secondly, yesterday the Washington Post published an opinion piece of mine on an unexpected topic: how to efficiently organize your calendar. If you are a knowledge worker, I think you will benefit from taking the advice I offer there.

Finally, I’d like to invite you to the first Changing Lanes livestream! I’ve published some interviews as transcripts in the past; the time has come to do some live in real time. My first guest will be , a co-author of my book The End of Driving, on the future of urban mobility, and the start-up he’s founded to build that future. Fair warning: Bern and I have some disagreements on this subject, which we will probe. I think it will be a fun conversation!

Tune in on Thursday, 28 May at 1200h EST. Subscribers will be notified when we go live, but you may also sign up here.

The only rational way to allocate scarce road capacity is price. William Vickrey worked out why in the 1960s: every car on a congested road imposes a small delay on every other car, without paying for it. Charge drivers an amount that offsets the cost they impose on everyone else, and the incentive to avoid peak hours sharpens; demand adjusts; trips get faster.

In North America, we have implemented road pricing in a few ways. There’s the congestion charge levied on vehicles entering southern Manhattan. There are some toll roads, like Ontario’s 407 ETR or the Pennsylvania Turnpike. The congestion charge is unique here, and toll roads, due to their unpopularity, are rare. Far more common is the managed lane.

A managed lane is a new lane built on an existing road, which is only accessible to people willing to pay to do so. That price isn’t fixed; it’s a dynamic charge that reflects demand, rising as more people use the lane and falling as fewer do, ensuring that the lane is always moving.

Managed lanes are one of the more successful transport innovations of the past thirty years. Drivers who need a fast, reliable trip can pay for it; drivers who are indifferent or cash-constrained can still use the free lanes to reach their destination. On the other side, the operator of the lane makes good money. Fitch, the ratings agency, has either upgraded or placed a Positive Outlook on eight managed lane facilities in the past thirteen months. Scott Monroe, Fitch’s senior director, calls managed lanes “the fastest-growing sector in ground transportation,” with appeal “across the ideological spectrum.”

So managed lanes work, under the right conditions. Unfortunately, there is a way that they can go very wrong. There is a vulnerability in the model that hinges on one clause, or rather the absence of one clause, in the concession contract. Given that some of these contracts run for ninety-nine years, getting the clause wrong has long-lasting consequences.

The vulnerability has a name: jam and harvest.

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Changing Lanes covers all aspects of mobility. See, for example:

• The Iron Law of Air Travel

• The Case for Transit Fare Enforcement

• Whatever Happened to the Uber Bezzle?

Today’s issue is about driving automation, and specifically a question Ross and I explored in our podcast conversation: who should pay when a self-driving car causes harm?

On 1 August 2025, Tesla lost $243 million because a court found its Autopilot to be defective.

The case was Benavides v. Tesla. In 2019, in Key Largo, Florida, George McGee, running his Tesla Model S on Autopilot, drove through a flashing red and a stop sign at roughly sixty miles an hour, killing Naibel Benavides and severely injuring Dillon Angulo. Under the Florida regime that applied at the time of incident, McGee was found 67% liable and Tesla 33%, which means that of the $129M in compensatory damages the jury awarded, Tesla’s share came to roughly $42.5 million. Bad enough; but the jury also awarded the plaintiffs $200M in punitive damages, which at the tame were not apportioned in Florida, but fell only on the party found to have engaged in the conduct warranting them, meaning Tesla bears them alone.1 Judge Beth Bloom denied Tesla’s post-trial motions on 19 February 2026. At time of writing, Tesla’s team has made no notice of appeal.

Tesla didn’t have to lose this much. Waymo, which has run more automated miles than any other operator, has never lost a verdict like this: not because it has avoided crashes, but because it has accepted in advance that operational liability for its driving system is its own.

How an automated-vehicle (AV) firm treats liability is telling, because liability is a hard, fast, and cheap sorting mechanism for distinguishing firms that are truly ready for public deployment from those that are bluffing. A manufacturer confident that its automated driving system (ADS) is safe will be willing to accept liability for incidents under that system’s control. A manufacturer that isn’t has reasons not to. Outsiders may lack the engineering sophistication to measure these vehicles directly. But anyone, including a regulator, can notice when a manufacturer won’t accept responsibility for its product.

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Waymo Accepts, Tesla Hides, Mercedes Pretends

For an example of what I mean, let’s look at three firms that make advanced driver-assist and automated-driving systems (ADAS and ADS, respectively) available to consumers.

Waymo offers customers rides in their own fleet of ADS-equipped vehicles. Its approach to liability is clear: it accepts operational liability, and acts as the legal operator in every market it deploys in. Even in Austin and Atlanta, where it acts in partnership with Uber and the latter firm handles all fleet logistics, Waymo retains responsibility for the “Waymo Driver”, i.e., the firm’s ADS. In all cases, riders will deal with one defendant if something goes wrong: the one that built the autonomy stack.

The track record matches this posture. Waymo’s most recent safety update, on 19 March 2026, reports a 92 percent reduction in serious-injury-or-worse crashes, an 83 percent reduction in airbag-deployment crashes, and an 82 percent reduction in any-injury crashes. That’s across 170.7 million rider-only miles through December 2025, against same-city human benchmarks. This is broadly consistent with earlier, peer-reviewed work (like Kusano and Schorr, Traffic Injury Prevention 2024 or Swiss Re/Waymo, Heliyon 2024), and the magnitudes are robust. It is the strongest safety evidence currently in hand for any commercially-operating ADS.

Waymo’s safety record isn’t spotless. I wrote earlier this year about the concerning incident in Santa Monica where a Waymo struck a child near a school. Separately, in Austin, the school district has documented at least twenty-five violations during the 2025–26 school year of Waymo vehicles passing stopped school buses with red lights flashing and stop arms extended. Waymo patched the software (in the language of automobile product safety, a ‘voluntary recall’) in December 2025, but violations continued through January 2026, with another in March.

The fact that we know as much about these incidents shows that the system works. Waymo reports promptly, the incident reports aren’t redacted, and bad code is getting patched through the recall mechanism. None of it is hidden.

Waymo makes its way to D.C. by Rob Pegoraro is licensed under CC BY-NC-SA 2.0

Meanwhile, Tesla pushes liability outward at every layer it can. The firm’s FSD (Supervised) owner’s manual reads, in operative part: “You are responsible for the speed and control of your vehicle at all times, whether FSD (Supervised) is enabled or not.” Under other circumstances, I wouldn’t object: an ADAS system is supposed to be a driver-assist feature, it’s right there in the name. Unfortunately FSD stands for Full Self Driving, and that name implies the vehicle doesn’t require a human’s input; the Benevides verdict depended in part on this confusion.

It gets worse. The Tesla vehicle purchase agreement imposes binding arbitration and a class-action waiver that seems designed to keep any customer claim out of a jury box. For Tesla’s Austin robotaxi service, which uses the firm’s ADS Full Self Driving (Unsupervised), Tesla has not publicly disclosed the structure of its commercial coverage.

The results are what one might expect from that posture: the firm is under pressure from regulators, and it seems less than cooperative with them. Leaving aside the Benavides verdict, NHTSA (the national USA regulator responsible for ensuring safety on American roads) upgraded its investigation into FSD behaviour in low-visibility conditions to a full Engineering Analysis on 18 March 2026, one step short of a recall demand. (I have written about this set of incidents for Asterisk.) A separate Preliminary Evaluation (PE25012) on FSD traffic-safety violations covers another 2.9 million. NHTSA has made an information request to Tesla to support that evaluation; Tesla has secured at least two deadline extensions on providing answers.

Meanwhile, in Austin, the firm’s robotaxi rollout is marred by incident after incident. AV and ADAS operators in the USA must follow NHTSA’s Standing General Order 2021-01 (hereafter SGO) a requirement to disclose crashes within set windows. Through mid-March 2026, the SGO records 15 reported crashes against approximately 800,000 cumulative paid-Robotaxi miles. Breaking that out, that’s about one crash per 57,000 miles, against Tesla’s own claimed human benchmark of one minor collision per 229K miles. This means that the Tesla service is crashing about four times higher than the human-driver benchmark Tesla itself sets.

In response to questions about that four-times-worse-than-humans framing, Tesla’s CEO, Elon Musk, has said only that the unsupervised program has recorded “no accident or injury… to date“. I suppose we’ll have to take his word for it, since all fifteen crash narratives are redacted as Confidential Business Information; unlike all other major AV operators, Tesla fully redacts its SGO narratives.

Finally, I used to cite Mercedes-Benz as an exemplar in this area, as a firm that has accepted liability for autonomous operation while its ADAS, DRIVE PILOT, is engaged. The framing came from a wave of trade-press coverage in March 2022, after Mercedes executives told Road & Track the firm would accept legal responsibility for what the car did under DRIVE PILOT. Road & Track‘s own gloss, which was “Once you engage Drive Pilot, you are no longer legally liable for the car’s operation until it disengages,” was what we all took at face value, myself included. Respect to for teaching us all otherwise, in his September 2023 piece “No, Mercedes-Benz will NOT take the blame for a Drive Pilot crash“. There, he noted that what Mercedes had actually committed to was product-defect liability (which statute imposes anyway) and not the tort liability that would matter in a wrongful-death suit.

What we all should have done was read the contract. The MBUSA DRIVE PILOT Subscription Terms (last updated 5 March 2024) leave the driver as the “fallback-ready user,” responsible at all times for their own actions, and limit MBUSA liability across “all claims, including, without limitation, claims in contract and tort (such as negligence, product liability and strict liability).” The customer’s insurance pays first; subrogation is waived; binding arbitration is required; participation in class-action suits is waived.

So Mercedes accepts product-defect liability, which it has anyway by statute, and not the tort liability that would matter in a wrongful-death suit. Koopman calls this a “moral crumple zone strategy,” borrowing the framing from Madeleine Clare Elish’s 2016 paper of the same name: the manufacturer reserves the option to blame the human driver for operational failures while accepting only the product-defect liability that statute already imposes.

Three firms, three postures, three different answers to the same question: when something goes wrong, who is on the hook? Engineering confidence is the cheapest hypothesis a regulator can test. This suggests a good way to proceed, namely making approval of a self-driving permit conditional on accepting full liability.

Don’t Liability Rules Favour Incumbents?

So far, so straightforward: an AV operator should accept liability for incidents under its system’s control, and a regulator should refuse to permit operators that won’t. Waymo demonstrates that the rule is workable at commercial scale; the rest of the industry demonstrates what happens when it isn’t applied. One might think that the case for an operators-pay rule writes itself.

Not everyone thinks so. The most academically serious counter-argument comes from Gary Marchant and Rachel Lindor’s 2012 article in the Santa Clara Law Review, “The Coming Collision Between Autonomous Vehicles and the Liability System”: strict manufacturer liability could make AV deployment uninsurable for smaller operators, entrenching incumbents and slowing beneficial deployment. The concern has force at the full-city ADS robotaxi tier, where AV insurance markets are thin and specialty underwriters dominate. The underwriting structure of the largest fleets is not public, which means that Marchant and Lindor’s concern may have force here.

There are two reasons to think that it does not. Firstly, history cuts against it. As one thinker we admire here at Changing Lanes, Prof. Bryant Walker Smith, has noted, in 1993 the received wisdom that advanced vehicle control systems, like adaptive cruise control, would be uninsurable without statutory limits on tort liability, but 25 years of subsequent rollouts of just such systems falsified the claim. Tort liability has proven flexible enough to permit innovation by manufacturers of all market capitalizations and sophistication.

Secondly, while I am sympathetic to the idea that strict regulation might serve as a barrier to entry, I think that in this case the relevant comparison is not between operators-pay and no-rule-at-all, but instead between two kinds of liability. Predictable, ex ante, contractually-defined manufacturer liability—what Waymo accepts in contract, and what Geistfeld and Abraham/Rabin have argued for in the law reviews—channels exposure into commercial insurance markets and lets entrants underwrite their risk. Unpredictable, ex post, jury-determined liability—what we might call the Benavides mechanism—does the opposite. A litigation lottery in which any operator might face $243M USD verdicts if a jury so chooses is worse for small operators, not better.

To be clear, there will always be a moat: it’s reasonable to think that a $200M punitive verdict would be fatal for a small firm, whether anticipated or not. But putting that liability upfront into insurance markets seems more likely to encourage competition than the alternative.

The States Must Lead

The rule itself is straightforward. If a manufacturer or operator claims its automated driving system is safe, it accepts 100 percent of liability for incidents occurring under that system’s control. Burden is later allocable to suppliers, sub-system manufacturers, or others if appropriate; that is a question between the operator and its supply chain, not the injured party’s problem. The injured party deals with one defendant.

In my view, the operative mechanism should be a state DMV permitting condition: a manufacturer applying for a deployment permit must accept liability for ADS-controlled operation as a condition of the permit, or will not receive that permit.2 [2] Tying the rule to a permitting decision avoids the Mercedes problem: a manufacturer cannot evade the rule by drafting subscription terms that disclaim the liability.

This argument has academic backing — Geistfeld in the California Law Review (2017), Abraham and Rabin in the Virginia Law Review (2019), and the IATR’s 2023 model framework which I have previously written about—but no jurisdiction has formally adopted it.

The near-term opportunity is in Texas. The state’s new Autonomous Vehicle Operation Permit regime under SB 2807 takes full effect on 28 May 2026; applications are open through the Motor Carrier Credentialing System. The certification requirements address operational compliance and minimal-risk capability—registration, insurance or self-insurance, federal compliance, a recording device, a first-responder interaction plan—but do not include an express liability-allocation condition. That is the gap an operators-pay rule would fill. The Texas DMV has authority under §545.453 to add such a condition by rule, without further legislation. Tesla holds a transitional Texas permit through August 2026; a DMV decision on Tesla’s renewal would be the most informative event of the year. It would show us a state regulator deciding, in writing, whether Tesla’s posture is acceptable.

In one sense, this may seem a great deal of fuss over nothing. Thanks to the Benavides decision, it’s clear that if an AV firm’s products are responsible for harm, the firm will be responsible for that liability; despite its attempts to evade accountability, Tesla will pay. The question is how AV firms will pay. Will it be predictably, contractually, up front, in exchange for procedural protections; or unpredictably, by jury verdict, in exchange for nothing?

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As I wrote in the very first issue of Changing Lanes, the posture firms take matters. Each redaction of a safety report; any disclaimer that fails to bind a third-party plaintiff; and every nine-figure fine that reads as a manufacturer made to pay against its will; all are fuel for backlash that will not stop at the bad operator. The technology has survived the Benavides verdict, and it has survived the death of a major firm (like Cruise).3 But it is not clear it can survive widespread conviction that the firms deploying it are taking sides against the public.

Confident manufacturers reveal themselves by accepting responsibility, as Waymo does. Unconfident manufacturers reveal themselves by refusing to accept it. They will discover, as Tesla did in Benavides, that their attempts to escape responsibility won’t save them. The best outcome is for AV firms to be smart and accept that liability up front.

If they won’t, our regulators should impose it.

The subject of today’s piece is California Forever. I met the firm’s CEO, Jan Sramek, at Progress Conference 2025, where the seeds of today’s piece were planted. I’m pleased to report that I will be attending Progress Conference 2026 in October, where I will be speaking on driving automation, alongside fellow speakers Dmitri Dolgov, the co-CEO of Waymo, and Ryan Oksenhorn, co-founder of Zipline. (Other speakers include two Nobel laureates and various other luminaries who don’t work on transport, but we won’t hold that against them.) There is no place like Progress Conference to learn about the future we deserve, and meet the builders who are making it happen. Attendance is by invitation; apply for one here.

My investigation When Was Peak Book?, formerly paywalled, is now available to all subscribers. I hope you enjoy it!

In the spring of 1947, William Levitt broke ground on 1,200 acres of Long Island potato farmland, with the aim of building cheap houses, fast, for returning veterans who needed somewhere to live. The resulting community, Levittown, had 17,000 homes on wide residential streets; it immediately became the template for how Americans built greenfield housing, and remains so today.

Levitt was not making a statement about the ideal type of urban form. His aim was only to build what people wanted as quickly and cheaply as he could. Since automobiles were omnipresent and land was cheap, he settled on curvilinear streets on generous lots, with no provision for walkable density.

That was three generations ago, but the legacy lives on. Nassau County, where Levittown was built, today remains almost entirely car-dependent, since its physical form does not permit sufficient transit for car-free living. On the scale of a human lifetime, the choices Levitt made were irreversible. So are the choices made by the innumerable developers who followed Levitt’s pattern.

On 15,000 acres of Solano County, California, roughly midway between Sacramento and San Francisco, Jan Sramek and his team are making their own irreversible choices today.

The company is called California Forever. Its CEO is Jan Sramek, a former Goldman Sachs trader and education entrepreneur who spent the better part of a decade assembling the land and the political coalition necessary for the project. Originally proposed as a new community, through the entitlement process, the city has now become an expansion of an existing city, Suisun (pronounced SOO-soon). A truly new American city, rather than a suburban master-planned community; a city built from bare ground on its own logic; that hasn’t happened at this scale in living memory, which makes it interesting indeed.

The project is complex and contested. It has its advocates (I am one) and its detractors (there are many), who clash over the impact of the project and the value it can add to California and the USA.

None of that is what this piece is about. This piece is about mobility.

Readers may know that I am one of the very few people who has been employed on a project to build a new neighbourhood, with the explicit responsibility of thinking through the mobility elements that would make it up, and how they should interact with housing and urban form. I have written about the conclusions I reached, and the experience of reaching them, before. So I am one of the very few who has parallel experience to what Sramek and company are doing now. Even so, my experience is a loose fit with what is happening in Suisun, because the Quayside project that I worked on featured roads, sewers, and much of its other infrastructure before we began to plan. In many cases we had to colour within the lines, but California Forever is much less constrained. Given that freedom, how bold will the vision be?

To answer that question, earlier this year, I sat down with Sramek to discuss, with the aim of understanding what sort of mobility system the California Forever team wants the Suisun Expansion to have, and whether its approach can bear scrutiny.

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Locking In the Right Form

New post-war American development locked in car dependency from the start, by designing for the car as the primary mobility mode. Putting the car at the top of the hierarchy means that many other choices are made immediately. These included wide arterials that tried to accommodate both throughput and access, and largely failed at both; surface parking lots that separated buildings from the street; and setbacks that made walking unpleasant.

These decisions cast the city in amber, or rather, in concrete. Changing any of these after the fact, assuming one could find the political support to do so, would require the physical reconstruction of billions of dollars of infrastructure. This has meant, in effect, that doing anything differently is impossible.

The decisions made at a city’s inception are more-or-less permanent. This means that the decisions California Forever makes about Suisun Expansion now, before construction, will be irreversible. And the first of these irreversible decisions is: the Expansion’s streets will be public realm first, and transport infrastructure second. “Fundamentally, we treat streets first as places for people to spend time in,” Sramek told me, “and second as places where mobility happens.”

The Specific Plan that governs the Expansion’s development encodes this into the physical fabric, with narrow rights-of-way (residential slow streets run as narrow as 20 feet), fine-grain block structure with parcel frontages of 16 to 25 feet, frequent building entries, and back alleys absorbing service functions. Designing this way is a deliberate foreclosure of car-centric possibilities, now and in the future.

The second irreversible commitment is the rapid-transit lane network. The Specific Plan mandates dedicated and physically-separated transit lanes, with stops every quarter-mile, on lines spaced half-a-mile apart, meaning that the Expansion residents and visitors will always be within walking distance of a good higher-order transit option.

Planners use a heuristic that people are willing to walk as far as 300m to a bus stop but 700m to a subway stop; put another way, the better the transit, the farther patrons are willing to walk to reach it. Whatever the technology, rapid transit in its own right-of-way is closer to a subway than to a city bus, so the Expansion placing lines a quarter-mile apart (just over 400m) seems like excellent provision to me.

When I first read up on California Forever, the network was going to consist of Bus Rapid Transit (BRT) lanes; as a former BRT network planner, I approved of this decision. When I learned these were being renamed as “RT” lanes, I worried; BRT remains, in my view, the best way to build cheap, effective urban rapid transit, but suffers from prejudice against the bus as a transport mode. Was California Forever giving in to irrationalism?

That concern turns out to be unfounded. The renaming indicates agnosticism on the California Forever team’s part on what mode should run in that lane; it will likely be shuttles in the early days, buses as the city grows, with possible conversion to a rail-based solution later (the lanes are being constructed to accommodate such a conversion in the future.)

The critical priority, as per Sramek, was reserving the space in the right-of-way; the technology that fills it is secondary. The first buses may be automated shuttles, which certainly caught my attention (more on this shortly). As the city grows and demand warrants it, those corridors can carry higher-capacity vehicles. The key thing, the irreversible decision, is to build protected rights-of-way first. Everything else is adjustable.

The third decision is the Expansion’s density. The Specific Plan sets a minimum residential density of 30 dwelling units per net acre. The reason for that figure is that it represents the minimum below which neighborhood retail struggles, and the passenger volumes don’t exist to sustain viable public transit at a frequent schedule. (It’s also the rough density of San Francisco at its urban core.) Locking in the right density floor before the first parcel sells should keep that floor constant in the future, ensuring that transit always has enough people nearby to support it, a policy I have advocated for in the past.

The final structural decision California Forever is making upfront is keeping the parking at the edges. Suisun Expansion will welcome cars at the city’s edges, in public garages at the city’s boundaries. Access to these will be priced dynamically at all hours, with the revenue directed toward funding the city’s transit and cycling infrastructure. By making the core inhospitable to parking, and using parking revenue to cross-subsidize other modes, the Expansion will permit car use but create strong and permanent incentives toward transit and active transportation.

Illustrative rendering of a Suisun Expansion block, from p. 72 of the Suisun Expansion Specific Plan.

Sramek exudes confidence that the choices the team is making are the right ones. His brio rests on a straightforward historical argument, which is that humans have had cities for thousands of years but the car for only twelve decades, meaning that building streets for people, not vehicles, is the more-respectable assumption to make. Cities built on the pre-car model remain, in his word, “beloved”, and so too will new ones.

None of this guarantees the outcome. Locking in good physical form is necessary but not sufficient. Density minimums and protected lanes create only some of the preconditions for transit-oriented urbanism.

That means the rest of the Expansion’s mobility strategy must furnish the remaining ones.

Escaping the Cold-Start Problem

Most people only change their travel habits when they move to a new residence, or change jobs. A brand new community, whether a new city or a new neighbourhood, therefore faces a stark problem:

A) If there is not a robust transit option for people to use when they arrive, they will simply drive everywhere. If transit arrives later, their habits will be set, and they won’t use it

B) If there is a robust transit option for people to use when they arrive, it will be hideously expensive to build and operate, because there will be initially very few users to provide offsetting fare revenue; this typically means that the transit provider can’t sustain the service

Most new neighbourhoods, given this set of circumstances, choose a third option:

C) Run a transit option, but a minimal service: long trips to the nearest hub, or low frequencies, or both. This is cheap to offer, but is not useful, so most people opt to drive, and low ridership numbers never support the case to build new service.

This is another manifestation of the Endless Emergency.

The obvious way to solve this problem is to choose B), and bite the bullet: pre-commit to running good service in advance of construction, as long as it takes and as much as it costs, to bootstrap the new line into viability.

It’s much easier said than done. Toronto has a ‘transit first’ policy on the books that amounts to this approach, but despite decades of new development along the city’s eastern waterfront, has never run better service than a few sad buses.1 All the residents and students who live and study there have therefore made the rational choice to drive.

Another way to finesse the difficulty of B) would be to foreclose the driving option by deliberately not providing driving infrastructure, like parking facilities or multi-lane roads. This would ensure a customer base for early transit and forego the immense cost of auto-centric infrastructure.

This is also much easier said than done: almost every place in North America requires a car to get to, so denying easy auto access to a new urban area seems like a concession that new residents would never accept.

Despite the difficulties, the Expansion is taking B), and using both approaches: pre-committing to transit, and imposing friction on private car use.

This is a heroic approach, but they are being smart about it. California Forever is designing the Expansion’s first neighbourhood to be one where everything is available without transit. When everything in the area is available on foot or by bike, a bus network is initially superfluous to a safe, legible pedestrian and cycling environment. That’s what the Specific Plan’s greenway network and fine-grain block structure aim to provide.

Later, as more neighbourhoods are built, it is the transit grid that will connect them. Sramek showed me a map of the planned network: a grid structure that allows any resident to reach anywhere in the city via a two-seat ride, moving along one axis and transferring to complete the trip on the other.

The Suisun Expansion’s planned transit network. Coloured lines indicate transit routes. Figure 4.38 (p. 115) of the Suisun Expansion Specific Plan.

At first glance, this may seem an obviously sensible approach. At second glance, though, concerns arise. The classic objection to grid networks is that most trips require the patron to board a vehicle, alight, wait, and board a different vehicle. This friction, which transport planners call the transfer penalty, is something that riders hate, so much so that on the margin it discourages transit trips in favour of direct rides, which transport planners call a one-seat ride. The obvious way to obtain one is by hiring a vehicle: yesterday a taxi, today an Uber, tomorrow a Waymo.

California Forever addresses this problem by tackling the transfer penalty directly and indirectly.

The direct approach is simply to keep frequency high. Transport planners measure frequency through headways, the amount of time that passes at a stop between the presence of two vehicles running the same route. The Specific Plan mandates 15-minute peak headways as a floor, which will mean a transfer wait averaging under eight minutes. Sramek cited Zurich and Tokyo as reference models here; both run grid-adjacent networks at high frequency, and neither has a meaningful transfer-penalty problem. A grid with frequent service works like an intersection with a well-calibrated traffic signal: the wait is predictable, so it is tolerable.

The indirect way to address the transfer penalty is by running a high-quality service. Riders consistently overestimate how long they will have to wait when they transfer, which seems to be a fixed feature of human cognition, and one that can’t be remedied. But another such feature which can be remedied is this: the worse the conditions in which passengers must wait—too cold or hot, dazzlingly bright or dark, dirty and/or vandalized—the worse their overestimations. By providing high-quality vehicles and shelters, with good wayfinding, rider discomfort will be reduced, and so will the transfer penalty.

One of the ways the vehicles will be high-quality is that they will, if possible, be automated.

Sramek believes that the Expansion’s initial transit shuttles will very likely be self-driving. (He didn’t mention it specifically, but the form factor and range of Tesla’s Robovan make it an obvious candidate.) Early embrace of shuttle automation is less about reducing the transfer penalty, though doubtless that will be welcome, and more about keeping costs low. By the time California Forever is ready to deploy them to the Suisun Expansion, automated shuttles should have a high capital cost but a low per-kilometre operating cost. In the Expansion’s early, low-density and low-ridership phases, sustainable operating costs will enable the frequent service that is prerequisite to success.

Not Car-Free, but Car-Optional

Suisun Expansion will not be a car-free city.

Sramek is explicit about this, and the Specific Plan reflects it. The goal is not a city where cars are excluded, but a city where transit and active transport options are sufficiently good that most residents choose them, most of the time. The obvious contribution here is the wall of perimeter garages. Cars are welcomed at the edges, parked in shared facilities, and residents complete their last-mile journey by transit, or perhaps by bike or foot.

This is how walkable pre-car cities used to function. The early Nero Wolfe novels, set in 1930s New York City, are perhaps the most accessible illustration of this today: on the (rare) occasions when Wolfe wants to take a car trip, his factotum Archie Goodwin must first walk a few blocks to a garage, pick up the car, and then drive it back to Wolfe’s brownstone. Goodwin, when he wants to travel through New York, simply walks. In the later novels, written after 1945, Goodwin simply parks the car right in front of the brownstone, and walks less. The difference is the friction of the intervening few blocks. A car in a garage adds just enough inconvenience to make travel alternatives attractive without removing the car’s utility altogether.

Suisun Expansion’s residents may have access to an amenity unavailable a century before: an automated car that can be remotely summoned to the residence. This feature would preserve the utility while maintaining the friction, which is the optimal arrangement. Perimeter parking is doing good work here.

Nonetheless Sramek is realistic, and expects that most residents will use their cars when taking trips outside of the Suisun Expansion, at least in the early and medium term. “The majority of people will drive,” he told me, “because they are in Northern California and that’s how people get around, even in existing cities. If people mostly walk, bike, and use transit within the Expansion, we still will have made a massive contribution to the region in terms of walkability and transit.”

I think he’s right about all of this; as much as Suisun Expansion is being designed to make car-free travel genuinely practical, it can’t change the fact that many residents will want to travel elsewhere in the region. For those trips, many (most?) people will drive. All the same, Suisun Expansion can help, and is considering how to do so. Options under discussion include running shuttles to the Suisun-Fairfield Amtrak station, San Francisco’s Transbay Terminal, nearby BART stations, and the Vallejo Ferry. Speaking only for myself, I think the private intercity bus market, which responds quickly to demonstrated demand, will be happy to help serve these destinations as well.2

Two Gaps to Fill

For all the good work that Sramek and California Forever have done, the transportation problems are not yet completely solved. I can see two gaps that need to be filled.

Firstly, goods delivery is unsolved, a fact that Sramek acknowledges. Last-mile delivery will be structurally difficult in a low-car environment. Conventional urban neighbourhoods can accommodate cube trucks and delivery vans, though in a clumsy and unsafe fashion: there are driveways, curb spaces, and sometimes wide lanes. In the Expansion’s narrow-street, high-pedestrian environment, such vehicles will have nowhere to go, meaning that deliveries don’t get made… or that the public realm will be obstructed.

There are a few paths forward. Delivery companies serving Suisun Expansion will be forced toward smaller vehicles, much as they do in old-world environments like Barcelona’s Gothic Quarter: vans rather than trucks. The Expansion can go further by requiring sufficient provision for freight in the building code, namely dedicated pick-up-and-drop-off zones for larger buildings, and/or adequate loading docks, optimized for easy entry and exit by vans. They can do the same for delivery drones on building roofs. The Specific Plan has some references to this, but more will be needed.

Failing this, they should talk early to entrepreneurs who want to help them deliver micro-hubs that would replace delivery to individual buildings within a block with delivery to a single touchpoint. Readers of Changing Lanes will remember my interview with freight expert Sandra Rothbard, who also worked with me at Sidewalk Labs, on the various ways new developments can accommodate freight delivery in an affordable and sustainable fashion; all apply very well to what California Forever is aiming to do.

The team is also thinking about commercial and industrial goods movement. A historic right-of-way running through the site—the old Sacramento Northern corridor, partially intact—offers the possibility for freight service from the Foundry and Shipyard, the new city’s industrial sectors, to the main line.

Secondly, the physical plan is ahead of the operational plan. The Specific Plan is detailed and serious on built form; it is less developed on the governance and financial architecture of transit operations. What the transit agency will look like in practice, how it will be funded at scale, and what triggers determine when routes are added and frequencies increased, are all underdeveloped.

This is not unusual for a project at this stage of development; design decisions must come first. But I note that it is matters like these that will determine whether transit-oriented design produces transit-oriented behaviour. Physical form creates the preconditions, but operational architecture is what activates them. Fortunately, the Specific Plan is doing the harder of the two jobs. The job ahead is easier. The TMA model is a promising first step, but it depends on employer and resident participation. A step in the right direction would be to require that all employers and residents join the TMA, much as college students are obliged to pay dues to the student society.

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Just as the residents of Levittown today live with the consequences of choices made in 1947, by people who are long dead, California Forever’s choices this year will outlast everyone making them. A resident of Suisun in 2075 will live in a physical environment shaped by the decisions Jan Sramek and his colleagues are making today. To their credit, they understand the opportunity before them, and their plan reflects it. They are moving decisively to lock in the preconditions for transit-oriented urbanism into the Expansion’s infrastructure.

You may think that Suisun Expansion, as described here, is not a place that you would like to live; that you’d prefer an auto-centric suburb, with wide lots, wide roads, and no friction to driving. That’s a reasonable preference, and one that deserves to be satisfied. Fortunately, it’s easy to satisfy: the choices Levitt made in 1947 have dominated for decades, and remain available to every developer breaking ground today.

Suisun Expansion is one of the few American projects in generations to make it differently, and allow people with a different set of preferences an affordable opportunity to live a rich, full life without needing a car.

I hope that, in its own way, it is as influential on our future as Levittown has been on our past.

Respect to for feedback on earlier drafts.