Autonomous Fleets Threaten Public Transit and Deepen Urban Sprawl

Not Just Bikes

Cities need car-less drivers rather than driverless cars, because autonomous fleets will cannibalize mass transit and induce gridlock unless municipalities implement road pricing and pedestrian protections.

AI-assisted summary of How Self-Driving Cars will Destroy Cities (and what to do about it) — original source. Check the original for full context.

Source published: 2024-11-10

Key ideas

• Over $160 billion in venture capital has poured into autonomous vehicles, incentivizing companies to deploy unvetted fleets onto municipal streets despite safety concerns. (1:18)
• Rather than technological shortcomings, hostile road engineering accounts for most traffic fatalities; adopting Sweden's Vision Zero street design could reduce US traffic deaths by more than 80% without autonomous technology. (11:05)
• Widespread autonomous vehicle deployment threatens to induce travel demand, leading to longer commutes, exurban sprawl, empty 'ghost cruising' to evade parking fees, and increased vehicle miles traveled. (19:16)
• To prevent urban destruction, cities must proactively implement dynamic per-mile road pricing, install modal filtering, build protected bike networks, and stop subsidizing car infrastructure. (48:33)

Detailed notes

## Background Published on YouTube by Not Just Bikes on November 10, 2024, this video essay investigates the consequences of autonomous vehicle technology on urban development. The video description provides an extensive bibliography of urban planning studies, municipal crash records, and related channel essays on car-centric infrastructure, while directing viewers to an ad-free version hosted on Nebula.

## TL;DR The video argues that autonomous vehicles (AVs), rather than solving congestion and traffic fatalities, threaten to accelerate urban degradation by incentivizing sprawl, increasing vehicle miles traveled, and undermining mass transit. Drawing parallels to mid-century highway construction and the venture capital rideshare model, it shows how AV deployment encourages anti-pedestrian infrastructure such as sidewalk fences and signal-free intersections. Comparing the car dependency of London, Ontario to the transit- and bicycle-oriented design of Utrecht, the essay contends that true road safety and universal mobility require human-scale street design rather than technological fixes. It concludes with actionable municipal recommendations, including dynamic road pricing, removing urban highways, and prioritizing active transportation over autonomous fleets.

## Atmosphere & style The presentation carries Not Just Bikes' signature sardonic and analytical tone, combining biting humor with an underlying moral urgency regarding road safety and corporate accountability. Stark historical parallels and technical deconstructions of fatal AV failures transition into eerie 3D visualizations of pedestrian-free, signal-less streetscapes, creating an uneasy look at an aggressively motorized future. This technological dystopia is sharply contrasted against tranquil, vibrant footage of Dutch cycle paths, leaving viewers with a persuasive, grounded sense of urbanist clarity.

## Bulletin - [01:18](https://www.youtube.com/watch?v=040ejWnFkj0&t=78s) Over $160 billion in venture capital has poured into autonomous vehicles, incentivizing companies to deploy unvetted fleets onto municipal streets despite safety concerns. - [11:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=665s) Rather than technological shortcomings, hostile road engineering accounts for most traffic fatalities; adopting Sweden's Vision Zero street design could reduce US traffic deaths by more than 80% without autonomous technology. - [19:16](https://www.youtube.com/watch?v=040ejWnFkj0&t=1156s) Widespread autonomous vehicle deployment threatens to induce travel demand, leading to longer commutes, exurban sprawl, empty 'ghost cruising' to evade parking fees, and increased vehicle miles traveled. - [48:33](https://www.youtube.com/watch?v=040ejWnFkj0&t=2913s) To prevent urban destruction, cities must proactively implement dynamic per-mile road pricing, install modal filtering, build protected bike networks, and stop subsidizing car infrastructure.

## Key takeaways - [01:18](https://www.youtube.com/watch?v=040ejWnFkj0&t=78s) Venture capital pressures force autonomous vehicle operators to deploy fleets prematurely, prioritizing investor returns over public street safety. - [02:33](https://www.youtube.com/watch?v=040ejWnFkj0&t=153s) Autonomous vehicles struggle heavily with software edge cases, repeatedly blocking active emergency services and failing in real-world scenarios. - [05:58](https://www.youtube.com/watch?v=040ejWnFkj0&t=358s) AV companies engage in heavy political lobbying for self-certification frameworks, immunity from moving violation citations, and reduced data transparency. - [11:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=665s) Traffic deaths in the US stem primarily from hostile road design like stroads, which can be dramatically lowered using proven street engineering rather than autonomous tech. - [14:27](https://www.youtube.com/watch?v=040ejWnFkj0&t=867s) Machine-learning systems trained on car-centric cities incentivize AV companies to lobby against municipal street reorganizations like bike lanes to avoid costly fleet retraining. - [17:03](https://www.youtube.com/watch?v=040ejWnFkj0&t=1023s) Following the ride-hailing playbook, robotaxi operators initially subsidize fares to undermine public transit before transitioning to profit-maximizing monopoly pricing. - [21:48](https://www.youtube.com/watch?v=040ejWnFkj0&t=1308s) Lower travel friction and the elimination of driving stress induce demand, encouraging longer exurban commutes and fragmenting passenger trips. - [25:19](https://www.youtube.com/watch?v=040ejWnFkj0&t=1519s) Corporate marketing for autonomous vehicles mirrors historical campaigns like GM's 1939 Futurama, falsely promising that new automotive products will resolve traffic gridlock. - [29:56](https://www.youtube.com/watch?v=040ejWnFkj0&t=1796s) Autonomous vehicle lobbies threaten public transit funding by promoting point-to-point private subscription fleets over high-capacity mass transit. - [34:02](https://www.youtube.com/watch?v=040ejWnFkj0&t=2042s) To preserve vehicle throughput against pedestrians who cause AVs to yield, automotive lobbies may advocate sidewalk fencing or pedestrian transponders, severely harming street vitality. - [38:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=2285s) Electric autonomous fleets fail to resolve pollution and noise issues, as vehicle weight amplifies non-exhaust particulate emissions and tire-pavement friction dominates noise at urban speeds. - [39:41](https://www.youtube.com/watch?v=040ejWnFkj0&t=2381s) Autonomous intersection models eliminate traffic signals in favor of high-speed vehicle interleaving, effectively severing surface crossings for pedestrians. - [46:15](https://www.youtube.com/watch?v=040ejWnFkj0&t=2775s) Utrecht demonstrates that universal accessibility and mobility are best achieved through active transit infrastructure and car-free design rather than speculative AI technology. - [48:33](https://www.youtube.com/watch?v=040ejWnFkj0&t=2913s) Cities must insulate themselves against autonomous vehicle saturation by enacting road usage pricing, modal filters, and protected infrastructure for pedestrians and cyclists.

## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=040ejWnFkj0&t=0s) Introduction: The Polarized Debate on Self-Driving Cars

Public discourse surrounding the future of autonomous vehicles tends to split into two extreme camps. On one side are the skeptics who dismiss the entire concept as a pipe dream and an overhyped tech-industry delusion that will never materialize in the real world. Yet in several American cities, anyone can open an app, hail a ride, and watch an empty car pull up to the curb and drive them autonomously to their destination. On the other side are techno-optimists who insist that autonomous vehicles (AVs) have arrived, will soon blanket every municipality, and are poised to magically cure every modern transportation woe—slashing road fatalities, eliminating traffic congestion, cleaning up the environment, expanding mobility to underserved populations, and revitalizing urban centers.

Both narratives miss the reality. Autonomous vehicles are fundamentally real, the underlying technology improves daily, and commercial fleets will inevitably enter every city in the near future. However, if these technologies continue along their current trajectory, the outcome will not be an urbanist utopia. As the host bluntly summarizes his thesis: “The technology is getting getting better every day, and, if these improvements continue on this track, they will fundamentally destroy the fabric of our cities.”

[01:18](https://www.youtube.com/watch?v=040ejWnFkj0&t=78s) Urbanist Optimism vs. Capitalist Realities

It is easy to understand why some urbanists feel cautious optimism about autonomous transit. The vast majority of chronic municipal dysfunctions stem directly from private automobiles: suffocating traffic jams, toxic air pollution, ambient noise, and deadly streets. Urban space is systematically squandered, leaving sidewalks squeezed, bike lanes absent, and parks paved over to make room for multi-lane arterial roads and sprawling surface parking lots. Furthermore, navigating a car-dominated city on foot or by bike exposes people to dangerous human behavior, from speeding to widespread distracted driving. Under those harrowing conditions, placing navigation in the hands of a computer algorithm appears on paper to be an obvious upgrade.

With rigorous regulation and intentional public planning, automated fleets might have contributed to safer cities. That benevolent outcome, however, is vanishingly unlikely when examined against the 20th-century historical precedent of automotive expansion and the brutal realities of venture capital. More than $160 billion has already been poured into autonomous vehicle development. That immense financial outlay creates an intense imperative for corporate backers to generate returns immediately, rushing untested vehicles onto municipal streets regardless of public readiness.

[02:33](https://www.youtube.com/watch?v=040ejWnFkj0&t=153s) Moving Fast and Breaking People

Witnessing a driverless car smoothly navigate the streets of San Francisco might convince onlookers that fully autonomous driving has arrived. These vehicles observe posted speed limits and appear to handle traffic cautiously without anyone seated behind the wheel. That appearance is largely a facade: the vehicles are not operating strictly by autonomous computation. As recently as November 2023, Cruise confirmed that its robotaxis required human intervention every four to five miles. When vehicles encounter unexpected scenarios, remote teleoperation centers must step in to rescue them. Footage reveals robotaxis paralyzed behind construction toilet trailers waiting for a remote operator to steer around them, or frozen through multiple traffic light cycles because the computer could not decide if it was safe to make a right turn, forcing frustrated human motorists to detour around them.

The software inevitably struggles with the long tail of edge cases and unusual urban occurrences. In engineering and software development, the initial 90% of a project consumes 90% of the timeline, while the final 10% takes the other 90%. Autonomous vehicles remain fundamentally rigid systems that commit bizarre blunders. At a San Francisco Waymo holding lot, dozens of autonomous vehicles repeatedly drove in tight circles and honked at one another at 4:00 AM for days on end, infuriating nearby residents. Far more dangerously, official municipal records document dozens of cases where robotaxis obstructed emergency services by blocking ambulances mid-transit and colliding with active fire trucks.

```mermaid flowchart TD accTitle: Autonomous Vehicle Failure and Public Resistance accDescr: The cycle showing technical limitations of autonomous vehicles, resulting public incidents, and community protests.

subgraph TechFlaws ["Technical Realities"] A["Driverless Perception Algorithms"] --> B["Remote Intervention Needed\n(Every 4-5 Miles for Cruise)"] A --> C["Edge Case Failures\n(Stall outs, phantom braking)"] end

subgraph UrbanHarm ["Real-World Disruptions"] B & C --> D["Blocked Ambulances & Fire Trucks"] B & C --> E["Erratic Behavior & Severe Collisions"] end

subgraph Backlash ["Public Response"] D & E --> F["Grassroots Protests & AV Sabotage\n('Coning' by Safe Street Rebel)"] F --> G["Corporate Pressure & Deregulation Lobbying"] G --> A end ```

The human cost of these deployment experiments escalated dramatically in October 2023. A human driver struck a female pedestrian in San Francisco, propelling her directly into the path of an oncoming Cruise robotaxi. While the autonomous system braked hard to reduce impact—reacting faster than a human driver might have—the system's fundamental lack of real-world comprehension turned tragic. Once the woman fell beneath the chassis, the car's sensors lost sight of her. Lacking the object permanence of a human toddler, the vehicle determined the roadway ahead was clear and attempted to pull over, dragging the trapped woman beneath its wheels. Cruise leadership subsequently attempted to conceal this footage from both regulators and the media.

- Estimated capital invested in AV development: over $160 billion. - Intervention frequency admitted by Cruise (late 2023): human teleoperator assistance required every 4 to 5 miles. - Observed system failures: phantom braking, blocking emergency services, trapping pedestrians under vehicles, and early-morning parking lot gridlock with continuous honking.

[05:58](https://www.youtube.com/watch?v=040ejWnFkj0&t=358s) Public Backlash, "Coning", and Regulatory Capture

Citizens never consented to having their public roadways converted into beta-testing grounds for multi-billion-dollar technology firms. This lack of consent has sparked protests throughout California, culminating in actions where an autonomous Waymo vehicle was set on fire. Grassroots organizations such as Safe Street Rebel have systematically documented self-driving fleets committing dangerous moving violations: running red lights, cutting off pedestrians, obstructing public transit buses, straddling bike lanes, blocking intersections, and driving uncomfortably close to elderly pedestrians. The marketing myth that programmed vehicles will reliably follow traffic regulations has dissolved under empirical scrutiny.

In response, Safe Street Rebel popularized direct-action campaigns like the "Week of Cone." Because autonomous vehicle perception engines are hardwired to treat traffic cones as immovable hazards, placing a standard traffic cone directly onto the vehicle's hood immediately paralyzes the car. This act of civil disobedience, dubbed "coning," renders the vehicle inert until field personnel intervene.

Tech executives routinely champion the Silicon Valley motto to "move fast and break things." As the host observes: “And maybe that broken thing will be your spine under a robotaxi, but that's a risk they’re willing to take.” Rather than admitting their software is not ready for prime-time deployment, autonomous vehicle firms have applied heavy political lobbying to shield themselves from accountability. They have secured self-certification frameworks, fought off mandatory safety-data disclosures, and supported legislation in California preventing police from issuing moving-violation citations directly to self-driving car operators.

[08:50](https://www.youtube.com/watch?v=040ejWnFkj0&t=530s) The Fatal Uber Crash and Algorithmic Blindness

Automated vehicles rely on an array of external sensors—cameras, radar, and lidar—to scan their surroundings. However, physical sensors are useless without the underlying software interpreting their data. Software engineers face a perpetual trade-off: prevent the vehicle from striking genuine obstacles, but ensure it does not execute emergency stops for benign artifacts, like floating trash bags or irrelevant roadside clutter. Striking that balance incorrectly can yield fatal consequences, such as when a Tesla operating in an automated driving mode slammed on its brakes on a freeway without cause, triggering an eight-car pileup.

This software limitation was laid bare in March 2018 in Tempe, Arizona, during the world's first recorded pedestrian fatality caused by an autonomous vehicle. An automated Uber test vehicle—a modified Volvo SUV—struck and killed Elaine Herzberg as she walked her bicycle across a multi-lane road at night. The vehicle's suite of sensors had picked up her presence well in advance of the crash, but the onboard classification software failed to understand what she was. The system erraticly toggled its internal classifications, labeling her alternately as an unidentified vehicle, then a bicycle, then shifting to an ambiguous "other" category, before deciding she was a stationary object outside the travel lane. The software only recognized that Herzberg was an actual hazard directly in the vehicle's path 1.2 seconds before impact—far too late to execute an emergency stop.

The terrifying implication of machine perception is clear: “So when a self-driving car starts driving toward you, you’d better hope it hasn’t detected you as ‘other’.”

- Date and location of the crash: March 2018 in Tempe, Arizona. - Vehicle configuration: Uber Advanced Technologies Group automated software mounted on a Volvo SUV. - Software perception timeline: toggled between contradictory categories ("vehicle", "bicycle", "other", stationary object) for seconds; calculated an imminent collision path just 1.2 seconds prior to impact.

[10:34](https://www.youtube.com/watch?v=040ejWnFkj0&t=634s) The Real Road Safety Issue: Flawed Street Design

Examining sensor failures and software classifications obscures the structural culprit behind pedestrian deaths: hostile roadway design. The Tempe crash did not occur in a vacuum; it occurred on an arterial street engineered precisely like a highway, complete with elevated speed limits and virtually no safe accommodations for people traveling on foot. The roadway sat directly between a commuter rail station and recreational hiking trails, ensuring pedestrian crossings would occur.

Compounding the hazard, the roadway median featured an asphalt cut-through that was intended exclusively for emergency vehicle access whenever nearby bridges were shut down. To any normal person navigating the area on foot, this paved strip appeared to be an intentional mid-block crosswalk. This design flaw lured pedestrians into crossing high-speed traffic lanes with no signal protection—a failure of traffic engineering that an autonomous vehicle's software proved incapable of navigating safely.

[11:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=665s) Hostile Infrastructure and the Real Road Safety Issue

The physical environment around the fatal 2018 Tempe, Arizona crash site reveals a structural contempt for pedestrians. The location was a natural crossing point regularly used by people, yet instead of installing an actual crosswalk, the city posted superficial “use crosswalk” signs that remain to this day. Making matters worse, in 2018 it was physically impossible to reach the designated crosswalk from that path due to dense landscaping and trees. Following the crash, the city’s retrofitted “solution” was replacing the brick roadway median with a rough stone surface deliberately engineered to be hostile to foot traffic. While a narrow opening was eventually cut through the cacti, reaching the legal crossing still requires walking more than 200 meters out of the way, on top of enduring lengthy signal waits to cross the multi-lane highway.

```mermaid flowchart TD accTitle: Evolution of Tempe Pedestrian Crossing accDescr: Progression of street infrastructure changes at the Tempe crash site from 2018 to the present.

subgraph State2018["2018 Conditions"] A["Natural pedestrian desire line"] B["No physical crosswalk"] C["Greenery and trees block access to signals"] A --> B B --> C end

subgraph Alterations["City 'Solutions' Post-Crash"] D["Median converted to rough, hostile stone path"] E["Hole cut through cacti landscape"] C --> D C --> E end

subgraph Reality["Modern Reality"] F["Pedestrians forced to detour 200+ meters"] G["Long signal wait times across highway"] E --> F D --> F F --> G end ```

This dynamic illustrates how American traffic engineering consistently prioritizes driver convenience at the expense of non-motorized road users, only to blame pedestrians when crashes occur. The scale of the carnage is immense: approximately 42,000 people are killed and hundreds of thousands are seriously or permanently injured in American car crashes annually. Self-driving car firms seize upon this slaughter by marketing safety as their primary virtue. Yet the fundamental problem lies in street design, specifically the prevalence of "stroads"—hybrid corridors attempting to combine high-speed traffic with destination access—which are ubiquitous across the United States and Canada but largely absent from cities in other developed nations. Known engineering approaches like Sweden's "Vision Zero" framework could eliminate the vast majority of these casualties without requiring any unproven gadgets:

> “In fact, if the US had roads as safe as Sweden they would cut their road fatalities by over 80%. Without any new technology at all.”

Because safe street designs demand slowing or restricting motor traffic, they are politically untenable in an automotive-dominated society. Moreover, street safety improvements generate no private corporate profit. Autonomous vehicle (AV) manufacturers are not public-interest organizations; their concern for human preservation ends the moment liability drops below the threshold required to sell hardware and software. Once regulators are appeased, the corporate pitch will inevitably normalize autonomous fatalities as an acceptable statistical improvement over human error.

- Around 42,000 fatalities and hundreds of thousands of life-altering injuries occur annually on US roadways. - Adopting Swedish Vision Zero roadway principles would reduce US road fatalities by over 80% without novel technology. - Self-driving developers care about safety only insofar as it secures regulatory approval and facilitates vehicle sales.

---

[14:27](https://www.youtube.com/watch?v=040ejWnFkj0&t=867s) Training Cars on "Easy Mode" and Exporting Car-Centricity

Autonomous vehicle operations have deliberately established their roots in hyper-car-dependent environments. Companies originally gravitated toward regions like Phoenix, Arizona, not merely for favorable weather, but because Phoenix represents "driving on easy mode." The metropolitan area is composed of one-mile square grid blocks with exceptionally wide roads, almost no operational restrictions on cars, near-universal driving rates, and an urban fabric exceptionally deadly to people on foot:

> “If anthropomorphic cars could design cities, they would design Phoenix.”

Even San Francisco, while more urban, transit-rich, and walkable than Sun Belt sprawl, remains profoundly car-oriented when judged against standard European urban design. This training bias poses an immense barrier for international deployment. Autonomous systems are explicitly calibrated to the behavioral norms of American drivers, who operate under the legal and spatial presumption that motor vehicles reign supreme over every other transport mode. Tech corporations are unlikely to undertake the painstaking, multi-year task of re-training their fleets for the narrow, complex streets of European towns; instead, market pressures will encourage cities abroad to sanitize and widen their streets to accommodate American autonomous navigation.

```mermaid flowchart LR accTitle: Autonomous Vehicle Training Lock-In Cycle accDescr: How training self-driving fleets on car-centric US streets creates political resistance to street modernization.

subgraph Training["Current Baseline"] A["Trained on wide American grids<br>(Phoenix, SF)"] B["Systems inherit car-first behavioral norms"] A --> B end

subgraph Deployment["Global Export"] C["Deployed to compact European / international cities"] B --> C end

subgraph LockIn["Municipal Gridlock"] D["City tries to remodel street<br>(transit, bike lanes)"] E["Car companies lobby against alterations<br>to avoid costly re-training"] C --> D D --> E E -.->|"Blocks changes"| D end ```

A far more insidious risk stems from the foundational architecture of these systems. Because AVs learn primarily through billions of data points gathered by human drivers on existing roadways rather than simple rule-following algorithms, modernizing urban layouts becomes far more difficult:

> “It won’t be enough to just put up a sign and update the rules of the road, governments will need to convince every self-driving car company to re-train their cars.”

Should a municipality attempt to claim road space for separated cycling tracks, widen sidewalks, or dedicate lanes to surface public transit, multi-billion-dollar AV firms backed by lobbying machines have a direct financial incentive to block those projects. Street networks risk becoming frozen in their current, car-dominated forms.

---

[17:03](https://www.youtube.com/watch?v=040ejWnFkj0&t=1023s) The Illusion of Cheaper Taxis and the Ride-Hail Playbook

Strip away high-tech rhetoric, and an autonomous vehicle is fundamentally an app-based taxi operating without a human driver inside the cabin. Believing that cheaper taxis represent a panacea for systemic metropolitan mobility failure ignores basic urban geometry and economic history. The autonomous industry is duplicating the venture-capital playbook pioneered by Uber and Lyft:

```mermaid flowchart TD accTitle: The Venture Capital Ride-Hail Playbook accDescr: The cycle of venture capital subsidies undercutting transit, followed by monopoly pricing.

subgraph Phase1["Phase 1: Market Saturation"] A["Massive venture capital subsidies"] B["Artificially low passenger fares"] C["Municipalities defund public transit for rideshare vouchers"] A --> B B --> C end

subgraph Phase2["Phase 2: Entrenchment"] D["Public transit eroded / competition weakened"] C --> D end

subgraph Phase3["Phase 3: Profit Extraction"] E["Venture capital dries up"] F["Fares aggressively raised to maximize investor returns"] D --> E E --> F end ```

In their expansion phases, ride-hailing services burned billions to keep passenger fares artificially low. This predatory pricing convinced multiple American municipalities to cut fixed-route public transit budgets in favor of subsidizing private ride-hail trips. Yet as soon as market dominance was achieved and capital markets tightened, fares surged. The assumption that removing the driver permanently lowers customer fares misapprehends how monopoly pricing operates:

> “They charge as much as possible to maximise profits and once they've eliminated or colluded with the competition they can charge whatever they want.”

Ceding municipal mobility networks to a consolidated cartel of autonomous software conglomerates will inevitably enrich corporate shareholders while degrading the travel options available to the broader public.

---

[19:16](https://www.youtube.com/watch?v=040ejWnFkj0&t=1156s) Parking Realities, Mobility Myths, and Induced Congestion

Promoters regularly assert that autonomous vehicles will clear away parking lots because self-driving cars can drop commuters off and depart. Yet personal car ownership persists precisely because drivers value personal storage, privacy, and immediate availability over hailing cabs. The notion that private owners will willingly lease their personal vehicles out as robotaxis during the workday ignores the unappealing reality of opening one’s personal vehicle to the smells and wear of the general public.

Consequently, privately owned autonomous cars will still need parking near their owners. If municipal parking fees are higher than the operating cost per mile, autonomous vehicles will simply be programmed to endlessly cruise surrounding city blocks, worsening ground-level traffic while their owners work or dine.

Claims of universal accessibility for disabled people are similarly overstated. Many disabled individuals require physical boarding assistance or help securing mobility devices within the vehicle—needs an unstaffed robotaxi cannot fulfill without an attendant. App-based services also demand credit cards and smartphones, excluding unbanked and non-digitized populations. Rather than delivering true universal mobility, robotaxis function as an expensive distraction from actual accessible mass transit.

```mermaid flowchart TD accTitle: The Autonomous Congestion Trap accDescr: The feedback loop of induced travel demand caused by cheaper or hands-free autonomous vehicles.

subgraph Intervention["AV Deployment"] A["Driverless tech promises reduced congestion"] B["Perceived cost and cognitive effort of travel drop"] A --> B end

subgraph Behavior["Traveler Response"] C["People take more trips"] D["Trips extend over longer distances"] B --> C B --> D end

subgraph Consequence["Structural Bottleneck"] E["Ghost cruising to avoid parking fees"] F["Induced demand overwhelms road space"] G["Net traffic congestion worsens"] C --> E D --> F E --> G F --> G end ```

The assertion that autonomous vehicles will cure traffic congestion contradicts basic transportation physics. Every historical reduction in travel friction induces more traffic:

> “Every single time that we have done anything to make transportation cheaper or more convenient, the inevitable outcome is that people travel more often, and they travel longer distances.”

Much like highway widening projects induce more driving through latent demand, making automotive travel passive and cheaper will incentivize longer commutes, redundant trips, and phantom vehicle cruising, ultimately worsening citywide gridlock.

- Privately owned AVs face an economic incentive to cruise local streets endlessly ("ghost cruising") to avoid paid parking garages. - Autonomous fleets still exclude vulnerable and disabled passengers who require physical boarding assistance or lack modern smartphones and credit accounts. - Induced demand dictates that reducing the friction or perceived effort of car travel inevitably generates greater aggregate vehicle miles traveled.

[21:48](https://www.youtube.com/watch?v=040ejWnFkj0&t=1308s) Traffic Congestion Will Be Even Worse

When Uber and Lyft entered cities, they claimed they would reduce traffic congestion, yet the exact opposite occurred: vehicle miles traveled increased significantly. This dynamic will worsen with robotaxis because people will hail them even more frequently, particularly while services remain heavily subsidized. While some argue that robotaxis will reduce the number of vehicles downtown by parking in peripheral lots and entering the city only when requested, that assertion ignores corporate incentives. In a competitive market, response time is paramount. People grow impatient waiting for an elevator; nobody will tolerate waiting 14 minutes for a robotaxi pickup. Consequently, self-driving car fleets park directly in the heart of cities like San Francisco.

```mermaid flowchart TD accTitle: The Subsidized Autonomous Vehicle Congestion Loop accDescr: Diagram illustrating how free street access and sub-divided personal trips drive up vehicle miles traveled and suburban sprawl.

subgraph Operations["Street-Level Dynamics"] FreeRoads["Free road usage & zero street user fees"] --> Circling["Cars circle blocks indefinitely to cut response times"] SplitTrips["Single family trips fragment into multiple robotaxis"] --> IncreasedVMT["Massive surge in Vehicle Miles Traveled (VMT)"] MicroDeliveries["Trivial on-demand deliveries replace consolidated errands"] --> IncreasedVMT end

subgraph LandUse["Urban & Suburban Sprawl"] IncreasedVMT --> TrafficCollapse["Severe gridlock on urban arterials and highways"] PassiveCommute["Passengers work/relax during long commutes"] --> ExtremeSprawl["Commuters move farther into peripheral countryside"] ExtremeSprawl --> InfraDebt["Suburban infrastructure liabilities expand & compound"] end ```

The economics of city streets make this dynamic far more destructive. Aside from gas taxes, there are virtually no user fees for utilizing municipal roadways. Future robotaxis will be electric, charged at private depots, and completely immune to fuel-based taxes. Because street access is free, operators have zero incentive not to keep their fleets circling city blocks continuously to minimize wait times. This massive influx of low-capacity vehicles will displace far more efficient modes:

> “As long as the roads are free to use there is zero incentive for these companies not to have robotaxis constantly circling the block so that they can respond to customers as quickly as possible.”

Individual travel patterns will fragment into multiple trips. Today, a suburban parent might drop one child off at elementary school, another at high school, and then proceed to an office in a single vehicle. With robotaxis, each passenger can be dispatched in an independent vehicle, turning one car trip into three. This trend is already unfolding in San Francisco. While independent youth mobility is desirable, running separate cars for every passenger worsens street capacity. The same issue plagues instant commerce. European cities have already documented the chaos of 10-minute delivery services, while gig couriers frequently take single-item trips, such as delivering a single tube of toothpaste. Autonomous logistics will supercharge this model, putting a separate car on the street for every minor errand.

Furthermore, autonomous travel will drive outward development. Just as the mass adoption of early automobiles triggered post-war suburban sprawl by untethering workers from their job centers, autonomous vehicles will detach commuters entirely. When drivers are freed from steering and can answer emails, handle paperwork, or attend conference calls, living in an inner suburb loses its necessity. Commuters will move out to remote cottages with cheap land and low municipal taxes. Funneling millions of long-distance commuters onto arterial networks will exponentially increase vehicle miles traveled, severely worsening the structural financial insolvency facing North American suburbs.

---

[25:19](https://www.youtube.com/watch?v=040ejWnFkj0&t=1519s) The Promised Future (Past and Present)

The autonomous vehicle industry markets a radically frictionless future. Industry promotions claim that vehicle-to-vehicle communication, seamless highway merging, platooning, and high-speed autonomous corridors will render existing traffic delays completely archaic. A corporate marketing video by Ford exemplifies this narrative: it presents the modern city as riddled with gridlock and inefficiencies—problems caused by car dominance in the first place—and promises that buying their next-generation vehicles will resolve them. In Ford’s rendered vision, the city suddenly accommodates futuristic trains, vacuum tubes, parks, e-bikes, blue skies, pedestrian plazas, and dynamic smart crosswalks that appear out of nowhere whenever a pedestrian chooses to cross.

> “Of course, these problems were caused by people using their cars in the first place, but don’t worry about that, because buying their new cars will fix everything, so it’s fine!”

These promotional concepts match the historical playbook of the automotive industry. At the 1939 New York World's Fair, General Motors unveiled its massive Futurama exhibit, designed to showcase the utopian city of 1960. Futurama featured life-sized urban mockups and an overhead ride showing visitors how advanced grade-separated motorways would eliminate vehicular delays by segregating cars from cross-traffic:

- **Futurama's Vision (1939):** Pedestrians were promised quiet, elevated footbridges above traffic, while high-speed highways below whisked personal cars safely into the metropolis without delay. - **The Mid-Century Reality:** The highways were constructed, but rather than relieving traffic, they induced unprecedented demand for personal vehicle travel. Elevated urban freeways shattered and divided historic neighborhoods, saturated city street grids with cross-town traffic, multiplied urban air pollution, and saddled municipalities with overwhelming infrastructure maintenance debts that modern cities now spend billions of tax dollars trying to demolish.

---

[28:04](https://www.youtube.com/watch?v=040ejWnFkj0&t=1684s) How AVs Will Destroy Cities

New transportation technologies invariably reshape the built environment when substantial profit is at stake. To prepare for autonomous vehicles, cities must recognize how these systems will alter urban form. Mass consumer adoption will begin in affluent suburbs across the United States and Canada, where drivers face lengthy commutes and road networks are simpler to navigate than complex urban cores:

> “So we need to seriously consider how AVs could negatively affect cities, so that we can prepare for them today.”

As safety records surpass those of human drivers, corporate lobbying will demand exclusive AV-only lanes on highways and suburban arterials. Suburban municipalities will seize on subsidized robotaxis to justify cutting or eliminating fixed-route public transit. Developers will introduce entire suburban enclaves accessible strictly by autonomous vehicles, creating a tech-enabled evolution of the modern gated community to enforce socioeconomic exclusion:

- **Suburban Growth:** Subdivisions will sprawl across remote land, requiring vastly extended utility runs for power, sewer, and water mains. - **Deferred Liabilities:** As in the mid-20th-century suburban boom, developers and local officials will welcome short-term debt and development cash, ignoring that catastrophic maintenance bills will come due decades later.

---

[29:56](https://www.youtube.com/watch?v=040ejWnFkj0&t=1796s) Eliminating Public Transit

Once autonomous vehicle operators exhaust suburban expansion, their business models will demand urban growth. In dense cities, their primary strategy will be dismantling the competition: public transportation.

This dynamic closely mirrors the history of American streetcar networks. During the 1920s, Los Angeles operated the world's most extensive electric streetcar system. As unmanaged private cars entered the streets, streetcars became trapped in mixed-traffic congestion. Rail transit could not maintain parity with a street system heavily subsidized by government road spending. Subsequently, private streetcar operators across the United States were bought up by National City Lines—a front consortium backed by General Motors, tire producers, and oil companies. National City Lines dismantled the rail networks and replaced them with motorized buses, eliminating public rail options to force consumer reliance on personal cars:

> “Because well-functioning public transit is a threat to car companies.”

Autonomous vehicle companies will follow this blueprint:

```mermaid flowchart LR accTitle: Transit Cannibalization Sequence accDescr: How autonomous vehicle firms target transit networks to force users into private subscriptions. A["Transit Underfunding & Delays"] --> B["AV Lobbying Against Rail Funding"] B --> C["Rail Right-of-Way Converted to AV Lanes"] C --> D["Public Transit Cancelled for Robotaxis"] D --> E["Captive Urban Subscription Market"] ```

AV operators will lobby governments to cancel capital rail projects, divert municipal funding away from transit agencies, and pitch door-to-door robotaxis as modern transit replacements. While operators will showcase token autonomous bus concepts, their revenue model relies on private passenger vehicles and pay-per-mile robotaxis.

Converting train corridors into autonomous vehicle rights-of-way causes a massive collapse in carrying capacity:

| Transit Corridor / Mode | Peak Daily Volume / Physical Footprint | |:--- |:--- | | **Toronto 18-Lane Highway (Hwy 401)** | Over 100 meters wide, carries **fewer total daily passengers** than a single subway track. | | **Single Subway Line** | Operates within a narrow right-of-way, moving **more passengers per day** than an 18-lane highway. | | **Brooklyn Bridge with Streetcars (Early 1900s)** | Moved over **420,000 people per day** with dual rail transit tracks. | | **Brooklyn Bridge for Cars Only (1950s–Present)** | Trolley tracks were removed in the 1950s; traffic has **never exceeded 180,000 people per day** since. |

Replacing space-efficient shared transit with low-occupancy vehicles will flood urban street grids with gridlock. Autonomous vehicle firms will respond by lobbying cities to designate major corridors as autonomous-only. While marketed under the guise of optimizing system efficiency and human safety, the real intent is to outlaw human drivers, eliminate transit alternatives, and convert urban populations into recurring software subscribers. An example of this strategy is the "Loop NYC" proposal pitched by a New York engineering firm, which envisioned designating critical city streets strictly for self-driving vehicles under the claim that algorithmic optimization would streamline urban throughput.

[32:52](https://www.youtube.com/watch?v=040ejWnFkj0&t=1972s) Consuming All Streets

Car company marketing suggests that autonomous vehicles (AVs) will allow road space to be recovered, imagining urban corridors blocked off entirely from car traffic and converted into lush, linear parks. In reality, autonomous vehicle companies depend on door-to-door convenience for commercial viability, meaning they cannot afford to surrender access to urban street networks. Instead of retreating from roads, AV lobbies will argue for access to pedestrian zones, asserting that computer-driven cars are safer than human operators and provide critical access for individuals with mobility challenges.

```mermaid flowchart TD accTitle: Autonomous Vehicle Urban Space Feedback Loop accDescr: Diagram showing how AV market dynamics lead to increased street consumption and parking infrastructure.

subgraph Dynamics["Street Saturation Dynamics"] A["AV Market Goal:<br>Door-to-Door Service"] --> B["Demand Access to All Streets & Pedestrian Zones"] B --> C["Zero Driver Labor Cost:<br>Continuous Cruising"] end

subgraph Congestion["Urban Space Consequences"] C --> D["Robotaxis Circle Blocks for Quick Dispatch"] C --> E["Private AVs Roam for Cheap Parking Rates"] D & E --> F["Surface Parking Converted to Solar Charging Hubs"] F --> G["Net Expansion of Automobile Footprint in Cities"] end ```

Without the operational cost of paying human drivers or pricing on road usage, robotaxis will circulate continuously around city blocks to preserve the fastest possible dispatch response times. Private AVs will cruise autonomously while owners work, hopping between locations to seek lower parking fees or cheaper electric charging rates. Former surface parking spaces will not become civic parks; they will transition into high-density charging hubs servicing fleets of private AVs and commercial robotaxis. Rather than shrinking the automotive footprint, autonomous fleets will require even greater municipal spatial concessions.

- AV business viability hinges on door-to-door transit, blocking efforts to pedestrianize corridors or install linear parks. - Cruising without passengers becomes cost-effective without labor expenses, worsening deadhead street congestion. - Parking structures will transform into charging stations rather than green space, preserving automobile priority.

---

[34:02](https://www.youtube.com/watch?v=040ejWnFkj0&t=2042s) Eliminating Pedestrians

The dynamic between automated software and foot traffic creates an operational bottleneck. As pedestrians discover that self-driving programming enforces a complete stop when encountering human obstructions, people will freely cross streets mid-block. AV operators will find their systems brought to a standstill by predictable yielding behavior. To maintain high vehicle velocity, operators will lobby municipalities to install physical barriers to ban mid-block crossings and fence off sidewalk edges along major transit arteries.

This historical policy pattern played out in Bamberg, South Carolina. Bamberg's traditional Main Street doubled as a state highway. Downtown pedestrian traffic frequently interrupted through-traveling vehicles, prompting town planners to widen the corridor and install longitudinal fence lines along the sidewalks to physically bar mid-block crossings. Car throughput improved immediately, but the enclosed, high-speed corridor drove foot traffic away. Within several years of project completion, every single retail storefront in downtown Bamberg shuttered, turning the commercial core into a ghost town.

The outcome contradicted the projections of local leadership, as the narrator observes: “This was a monumentally stupid idea of course, but I bring this up because before the project, the director of the chamber of commerce said that the project will, quote, ‘be a major boost to the economy for the county and downtown Bamberg.’” Traffic engineers frequently operate under the assumption that expedited vehicular throughput bolsters local retail, ignoring that cars do not make retail transactions—pedestrians do. Confining pedestrians behind fences alongside high-speed automated traffic creates hostile streetscapes that destroy street-level civic life.

- Bamberg, South Carolina installed sidewalk fencing to prevent street crossing, resulting in the eventual closure of all downtown retail shops. - High-speed AV corridors require physical pedestrian fencing to prevent autonomous safety systems from halting traffic. - Eliminating foot accessibility diminishes local commercial districts, exchanging street vibrancy for vehicular throughput.

---

[36:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=2165s) Eliminating Speed Limits and the Modern "Jaywalking"

With public transit dismantled and pedestrians boxed out by protective barricades, autonomous vehicle developers will push to abolish municipal speed limits. The central justification will be that speed restrictions are arbitrary artifacts created for human reaction delays rather than millisecond computer processing. Removing speed caps will temporarily boost corridor throughput, which transportation authorities will celebrate as an operational triumph. However, higher travel speeds dramatically increase fatality rates for cyclists and pedestrians, because vehicle braking distance remains fundamentally governed by kinetic laws that software reaction times cannot override.

```mermaid flowchart LR accTitle: Historic vs Modern Pedestrian Displacement Strategies accDescr: Historical progression showing how the automotive lobby shifted collision culpability from drivers to pedestrians.

subgraph Century20["1920s Pedestrian Marginalization"] A["1920s Public Backlash:<br>High Pedestrian Fatalities"] --> B["Municipal Proposals for<br>Speed Governors & Fines"] B --> C["Automotive Lobby Inverts Blame:<br>Creation of 'Jaywalking'"] end

subgraph Century21["21st-Century AV Marginalization"] D["High-Speed AVs Cause Pedestrian & Cyclist Deaths"] --> E["AV Industry Shifts Liability to Non-Car Users"] E --> F["Mandated Wearable Transponders & LIDAR Reflectors"] end ```

Public outrage over crashes will mirror the anti-car sentiment of the 1920s, when rising vehicular fatalities spurred cities to propose mandatory mechanical speed governors and severe reckless driving fines. In that era, the automotive lobby countered public opposition by inventing and aggressively publicizing the concept of "jaywalking," effectively shifting legal and moral culpability from motorists onto victims. In the autonomous vehicle era, this paradigm will shift responsibility through wearable technology. Pedestrians will be expected to wear tracking transponders or LIDAR-reflective patches when walking near public roads, ensuring that crash investigations focus on whether the pedestrian properly transmitted their coordinates rather than addressing vehicle speed within urban spaces.

- Urban speed caps will face industry pressure for abolition under the claim that algorithmic perception eliminates driver human error. - Kinetic braking limits remain unchanged regardless of reaction speeds, elevating pedestrian and cyclist collision lethality. - The automotive lobby previously deflected public safety backlashes in the 1920s by manufacturing the concept of "jaywalking." - The modern equivalent threatens to be wearable electronic transponders or LIDAR tags, shifting collision fault onto unprotected pedestrians.

---

[38:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=2285s) Pollution and Noise

Fleet electrification will fail to eradicate the environmental damage associated with automotive volume. Although zero tailpipe emissions improve roadside air quality, a primary proportion of urban particulate pollution stems from mechanical tire abrasion, brake wear, asphalt degradation, and pulverized road markings. Particulate emission volumes scale upward with vehicle mass and travel velocity. Because autonomous vehicles incorporate heavy sensor arrays, computing platforms, and structural reinforcements, their increased weight, combined with higher travel speeds, will generate high particulate concentrations along AV express corridors.

| Environmental Factor | Internal Combustion Vehicles | Electric / Autonomous Vehicles | Real-World Urban Consequence | |:--- |:--- |:--- |:--- | | **Tailpipe Emissions** | High ($CO_2$, $NO_x$, particulate) | Zero direct exhaust emissions | Eliminates exhaust, but leaves non-exhaust particulates unaddressed. | | **Non-Exhaust Particulates** | Baseline tire, brake, and asphalt wear | Increased microparticle shed due to higher vehicle curb weight | Heavier AVs and faster speeds accelerate roadway and tire degradation. | | **Acoustic Signature** | Dominated by combustion engine below 50 km/h | Engine noise eliminated; tire noise unchanged | Above 50 km/h, road tire friction drowns out engine sound regardless of powertrain. |

Similarly, electric powertrains do not resolve traffic noise. Above roughly 50 kilometers per hour, tire friction against pavement out-volumes internal combustion powertrains. Even in locations like Oslo, where electric vehicle adoption is widespread, pedestrian overpasses across multilane corridors remain loud due to high-speed tire friction. As heavier, computer-operated cars accelerate down converted surface streets, ambient noise will reach decibel levels that trigger chronic physiological stress responses in nearby residents, rendering adjacent pedestrian environments unusable.

- Non-exhaust particulate matter—generated from tires, brakes, and roadway wear—increases with vehicle weight and operational speed. - Above approximately 50 km/h, tire-pavement contact produces more ambient noise than an internal combustion engine. - High EV penetration in cities like Oslo has not resolved highway corridor noise pollution.

---

[39:41](https://www.youtube.com/watch?v=040ejWnFkj0&t=2381s) Eliminating Traffic Lights

The push for vehicular throughput culminates in the elimination of conventional traffic signals. Over a decade ago, researchers at the University of Texas at Austin published demonstration models for Autonomous Intersection Management (AIM). The protocol modeled autonomous vehicles interleaving through high-speed intersections at full velocity without stopping, using machine-to-machine communication. While mathematically efficient for passenger throughput, it turns the street surface into an impassable, continuous stream of high-speed vehicles that completely excludes pedestrians and cyclists.

The narrator recalled his immediate impression when first viewing the concept: “This is the animation that made me really think twice about the future of self-driving cars. Because when I looked at it, the first thing that crossed my mind was, ‘huh. It would really suck to have to cross this intersection while walking or cycling.’”

```mermaid flowchart TD accTitle: Urban Segregation via Autonomous Intersection Management accDescr: Progression from continuous autonomous traffic flow to neighborhood severance and monopolized transit.

A["Autonomous Intersection Management (AIM) Eliminates Traffic Signals"] --> B["Continuous High-Speed Traffic Precludes Surface Crossings"] B --> C["Compensatory Pedestrian Infrastructure:<br>Ramped Concrete Overpasses"] C --> D["Neighborhoods Physically Severed into Inaccessible Islands"] D --> E["Walking & Cycling Become Infeasible"] E --> F["Monopolized Urban Mobility:<br>Residents Dependent on Paid AV Fleet Subscriptions"] ```

To quell public blowback over neighborhood severance, authorities will offer compensatory infrastructure via grade-separated pedestrian bridges. However, past highway construction in New York City demonstrates that such overpasses function as punitive, noisy bypasses designed to keep human beings from hindering traffic flow below. Pedestrians must climb switchback ramps into chain-link enclosures, exposed to ambient particulate pollution and road noise. Dividing urban grids with grade-separated AV corridors leaves neighborhoods isolated. By destroying safe pedestrian movement, bicycle networks, and public mass transit, private AV operators gain a monopoly over urban mobility, giving them unchecked power to inflate transit fares across entire metropolitan populations.

- University of Texas at Austin’s Autonomous Intersection Management (AIM) model removes traffic lights in favor of continuous vehicle interleaving. - Uninterrupted intersection movement eliminates the breaks in traffic required for street-level pedestrian crossings. - Pedestrian overpasses built over high-speed corridors serve to clear vehicle paths while subjecting pedestrians to lengthy ramps, noise, and fumes. - Eliminating walkable alternatives gives autonomous fleet networks a closed monopoly on local transportation.

---

[42:16](https://www.youtube.com/watch?v=040ejWnFkj0&t=2536s) Do We Actually Need AVs? Utrecht vs. Fake London

The perceived necessity of the autonomous car stems from the car-dependent environments common in suburban North America. Growing up in London, Ontario, Canada—a municipality the narrator refers to as "Fake London"—reveals how suburban land-use policies enforce vehicular reliance. Fake London features placename homages like the Thames River, Oxford Street, and Covent Garden Market, yet lacks genuine urban fabric. Arriving by passenger rail places travelers onto a high-speed stroad fronting asphalt surface parking lots. The urban core is hollowed out, the urban boundary is sprawled, transit buses operate on slow, infrequent schedules, and cycling feels unsafe. Daily errands require driving along dangerous, multi-lane stroads where crashes and traffic deaths are a regular occurrence.

```mermaid flowchart TD accTitle: The Car Dependency Solipsism Loop accDescr: Flowchart contrasting how car-centric design breeds high-tech vehicle fixes versus human-scale planning.

subgraph FakeLondon["Suburban North America: Fake London"] FL1["Sprawling Land Use & Stroads"] --> FL2["Unreliable Public Transit & Hostile Cycling"] FL2 --> FL3["Driving Compulsory for Daily Errands"] FL3 --> FL4["Traffic Congestion & Road Fatalities"] FL4 --> FL5["Apparent Necessity:<br>Self-Driving Cars to Automate Miserable Commutes"] end

subgraph Utrecht["Human-Scale Urbanism: Utrecht"] UT1["Compact Land Use & Traffic Evaporation"] --> UT2["Extensive Bike Infrastructure & Reliable Rail"] UT2 --> UT3["Driving Rendered Unnecessary"] UT3 --> UT4["Safe, Walkable Streets & Minimal Fatalities"] UT4 --> UT5["Technological Panaceas Like AVs Become Irrelevant"] end ```

Under these conditions, turning personal transportation over to vehicle computers seems like an appealing solution to stressful daily commutes. Yet this approach frames a built-environment failure as a computer software problem. The contrasting paradigm is Utrecht, a municipality in the central Netherlands with a population comparable to Fake London. A century ago, both cities possessed compact, human-scale footprints with similar street designs. Over the decades that followed, Fake London razed its historical fabric to accommodate high-speed vehicular traffic, while Utrecht preserved its historic core and built out dense transit networks and protected bicycle infrastructure, keeping mobility options broad and streets accessible without requiring automated driving.

- London, Ontario ("Fake London") features disconnected urban sprawl, underfunded transit networks, and stroad environments that make driving compulsory. - The impulse to automate personal driving is a coping mechanism for hostile, car-dependent infrastructure. - Utrecht shares an equivalent municipal population with London, Ontario, and historical photos show both were comparably walkable century ago before their planning paths diverged.

[44:04](https://www.youtube.com/watch?v=040ejWnFkj0&t=2644s) Utrecht vs. Fake London: Two Paths from the Same Car-Centric Past

Both Utrecht and London, Ontario ("Fake London") were founded long before the automobile, originally growing around mixed-use neighborhoods linked by streetcar networks. Over the course of the 20th century, however, both cities went down the same destructive path: embracing car supremacy, widening thoroughfares, bulldozing neighborhoods, and demolishing parts of their historic cores to erect suburban-style indoor shopping malls—the first of their kind in their respective nations. Utrecht even filled in its historic central moat canal (the Catharijnesingel) to build a multi-lane sunken expressway. Utrecht was about a decade behind London in executing these urban renewal projects, but otherwise tracked the exact same car-centric trajectory.

```mermaid flowchart TD accTitle: Divergence of Utrecht and Fake London accDescr: Historical progression comparing Utrecht and London Ontario from shared origins to opposite urban design outcomes.

subgraph Past["Shared 20th-Century History"] A["Pre-Automobile Era:<br/>Mixed-use & streetcars"] --> B["Mid-Century Modernization:<br/>Canals/homes bulldozed for urban highways & malls"] end

subgraph Divergence["The 1990s Turning Point"] B --> C["Fake London (Ontario):<br/>Continued car dependency, stroads & surface parking"] B --> D["Utrecht (Netherlands):<br/>Deliberate pivot to people-first infrastructure"] end

subgraph Present["Modern Utrecht Outcome"] D --> E["Highway restored to historic canal"] D --> F["Busiest train station (200k+ daily users)"] D --> G["World's largest bike garage (12k+ spaces)"] D --> H["Low noise, independent mobility for all"] end ```

The split came around the 1990s, when Utrecht made a conscious choice to reverse course due to mounting public alarm over the environmental and social consequences of car dependence. The city committed to reclaiming public space, slashing motor vehicle traffic, and prioritizing pedestrians and cyclists. In a dramatic act of urban repair, the sunken highway wrapping around the city center was excavated and restored back into a flowing canal, erasing all obvious traces of the concrete trench. Today, Utrecht's central shopping complex integrates seamlessly with the surrounding historic core on one side and connects directly through a wide pedestrian plaza to a modernized central railway station on the other.

Arriving by train in Utrecht highlights the stark gulf between the two cities. Despite having nearly the same population as Fake London, Utrecht Centraal is the busiest railway station in the Netherlands, carrying over 200,000 passengers each day across more than 1,000 national and international departures. The station anchors an expansive public transport network—including modern light rail trams—with hundreds of destinations within an easy walk. Directly beneath the terminal sits the world's largest bicycle parking facility, housing over 12,000 bikes. Travelers can tap a transit smart card, unlock one of hundreds of shared OV-fiets rental bicycles, and pedal anywhere in complete comfort.

- Utrecht and London both demolished city center fabric for suburban-style shopping malls, representing the first facilities of that design in their respective countries. - Utrecht Centraal handles over 200,000 daily travelers and over 1,000 train departures per day. - The underground bicycle garage beneath Utrecht Centraal accommodates more than 12,000 bicycles.

[46:15](https://www.youtube.com/watch?v=040ejWnFkj0&t=2775s) Car-Less Drivers Over Driverless Cars

Cycling and walking through Utrecht feel effortless because the built environment is designed to minimize car interference. Speed limits are strictly curbed, motor traffic volumes are kept exceptionally low, and main corridors beside the railway hub are restricted strictly to walking, cycling, and public transit. Along one of the busiest cycling paths in the world, the sheer volume of cyclists passing by in five minutes easily eclipses what someone might see over an entire lifetime living in Fake London.

The streets are quiet, animated by storefronts and sidewalk cafes rather than asphalt wastelands. Surface parking lots have been eliminated from the center, reinforcing the principle that cities are not inherently loud—cars make them loud. Because people are given high-quality alternatives, nobody is forced behind the wheel; only those who truly need or genuinely want to drive do so. This punctures the common Silicon Valley pitch that autonomous vehicles are indispensable for unlocking mobility for children, the elderly, and disabled individuals. In Utrecht, people across every age and mobility level already navigate the city autonomously on foot, on adaptive bikes, or via public transit. As the speaker highlights:

> “Because universal access to mobility isn't a fundamental issue: it's a problem caused by car dependency.”

Utrecht is not without flaws, and lingering scars of 1960s urban renewal remain visible. Yet the city solved the very mobility crises that autonomous vehicles promise to address without pinning its hopes on speculative artificial intelligence, without sinking hundreds of billions of dollars into unproven tech, and without ceding its civic streets to the algorithms of private corporations. Flooding those vibrant streets with self-driving cars would actively degrade them. As the speaker summarizes:

> “So it seems what we really need is not driverless cars, it's car-less drivers.”

[48:33](https://www.youtube.com/watch?v=040ejWnFkj0&t=2913s) Fortifying Cities Before the Autonomous Onslaught

To protect urban spaces from the threat of autonomous vehicle (AV) congestion, cities should treat Utrecht as a functional blueprint and aggressively reshape their street networks before AVs achieve widespread commercial deployment. First, municipalities must place strict geographic limits on where private automobiles can travel. While cities like Utrecht preserve essential vehicular access for deliveries, emergency responders, and residents with disabilities, passenger cars should be barred from cutting through downtown cores. Urban freeways dividing neighborhoods must be dismantled and converted into housing, parks, and local businesses.

Transit networks need modal filtering so that the fastest, most direct route across a city center is reserved exclusively for walking, cycling, and mass transit. Simultaneously, speed limits must be reduced immediately to cut down noise, limit pollution, and lock in road safety before corporate lobbies can push for higher autonomous operational speeds. Once lower speed limits are established, public support to maintain them is nearly universal.

Parking policy requires an immediate transformation. Municipalities must stop financing new multi-story parking garages—taking AV promoters at their word that privately owned parked cars will soon be obsolete—and begin converting existing surface lots into dense, productive mixed-use infill. Sidewalks and protected bike lanes should be mandated by standard street design manuals on every new build. Transit infrastructure must focus on modes that cannot easily be cannibalized by car lanes, like dedicated rail, trams, and busways under strict democratic, public oversight.

Crucially, road pricing must be implemented to stop empty autonomous vehicles from cruising endlessly to evade parking fees or zero-fare periods:

> “And most importantly of all, and I cannot stress this enough, we need to put a price on driving.”

With electric vehicles eroding conventional gas tax revenues, governments should institute dynamic road usage pricing that charges vehicles per mile traveled, scaling rates upward during peak travel periods. If cities implement these safeguards, autonomous vehicles can be deployed selectively on the public's terms where genuinely helpful, rather than where they maximize tech profits. And even if self-driving technology turns out to be an overhyped pipe dream that never achieves mass adoption:

> “And if the naysayers are correct, that self-driving cars really are just a pipe dream, and they never reach mass-adoption, then I guess we'll do all that work and just be left with beautiful, functional, efficient, and sustainable cities accessible to all.”

- Ban through-traffic in core neighborhoods using modal filters; motor vehicles should navigate around cities, not slice through them. - Tear down dividing urban freeways to build housing, parks, and commercial spaces. - Cease all new municipal parking garage construction and systematically repurpose surface parking lots. - Institutionalize protected bike tracks and wide sidewalks as baseline, mandatory requirements for street construction. - Prioritize rail, tramways, and protected transit rights-of-way over bus routes vulnerable to lane reallocation. - Replace declining fuel taxes with dynamic congestion- and distance-based vehicle travel fees.

[51:53](https://www.youtube.com/watch?v=040ejWnFkj0&t=3113s) Creator-Owned Media: Supporting Independent Urbanism on Nebula

Viewers looking to explore broader urban design topics can find complementary coverage from channels like *City Beautiful*, *City Nerd*, and *RMTransit*. *City Beautiful*, for instance, provides a detailed analysis of the exact regulatory and planning blueprints used by municipal leaders in his video, "How to Remove a Highway."

All of these creators, along with Not Just Bikes, publish their work on the independent streaming service Nebula. Described jokingly as "like Netflix … but for people who love trains," Nebula offers an ad-free, sponsorship-free viewing experience with early releases and platform originals like the competition show *The Getaway* and Abigail Thorn's film *Dracula's Ex-Girlfriend*.

Because Nebula is directly owned and operated by creators rather than media conglomerates or venture capital investors, revenue directly funds ambitious physical productions—including the on-location shooting and custom 3D environmental animations that made this deep-dive documentary possible. Subscriptions are available at $60 per year, or $36 annually (a 40% discount) via `go.nebula.tv/notjustbikes`, alongside a $6 monthly option. Active subscribers also receive one guest pass per month (accessible via the blue balloon icon) to grant a friend a free seven-day trial, and gift subscriptions can be purchased using standard payment cards or the Dutch payment system iDEAL.

## Notable quotes > [46:15](https://www.youtube.com/watch?v=040ejWnFkj0&t=2775s) So it seems what we really need is not driverless cars, it's car-less drivers. — Not Just Bikes

> [19:16](https://www.youtube.com/watch?v=040ejWnFkj0&t=1156s) Every single time that we have done anything to make transportation cheaper or more convenient, the inevitable outcome is that people travel more often, and they travel longer distances. — Not Just Bikes

> [11:05](https://www.youtube.com/watch?v=040ejWnFkj0&t=665s) In fact, if the US had roads as safe as Sweden they would cut their road fatalities by over 80%. Without any new technology at all. — Not Just Bikes

## Mentioned Cruise, Waymo, Uber, Lyft, Tesla, Volvo, Ford, General Motors, Safe Street Rebel, Elaine Herzberg, Futurama (1939 New York World's Fair), National City Lines, Highway 401, Brooklyn Bridge, Loop NYC, Bamberg, South Carolina, University of Texas at Austin, Autonomous Intersection Management (AIM), London, Ontario, Utrecht, Catharijnesingel, Utrecht Centraal, OV-fiets, Nebula, City Beautiful, City Nerd, RMTransit, Abigail Thorn, Not Just Bikes, iDEAL

## Video description Support Not Just Bikes by signing up to Nebula: http://go.nebula.tv/notjustbikes

Watch this video ad-free and sponsor-free on Nebula: https://nebula.tv/videos/notjustbikes-how-selfdriving-cars-will-destroy-cities

Patreon: https://patreon.com/notjustbikes Mastodon: @notjustbikes@notjustbikes.com NJB Live (my live-streaming channel): https://youtube.com/@njblive

--- Related Videos

Stroads are Ugly, Expensive, and Dangerous (and they're everywhere) [ST05] https://nebula.tv/videos/not-just-bikes-the-ugly-dangerous-and-inefficient-stroads-found-all-over-the-us-canada-st05 https://youtu.be/jN7mSXMruEo

More Lanes are (Still) a Bad Thing https://nebula.tv/videos/notjustbikes-more-lanes-are-still-a-bad-thing https://youtu.be/CHZwOAIect4

Cities Aren't Loud: Cars Are Loud https://nebula.tv/videos/not-just-bikes-cities-aren-t-loud-cars-are-loud https://youtu.be/CTV-wwszGw8

--- References & Further Reading

Safe Street Rebel - Not without a fight https://www.safestreetrebel.com/

Person dies after 2 driverless cars block ambulance on way to hospital https://www.scrippsnews.com/us-news/person-dies-after-2-driverless-cars-block-ambulance-on-way-to-hospital

Explore: See the 55 reports — so far — of robot cars interfering with SF fire dept. https://missionlocal.org/2023/08/cruise-waymo-autonomous-vehicle-robot-taxi-driverless-car-reports-san-francisco/

What is Vision Zero? https://visionzeronetwork.org/about/what-is-vision-zero/

Uber Takes Us for a Ride https://www.powerswitchaction.org/resources/uber-takes-us-for-a-ride

Robotaxis Won’t Get Us There, So Let’s Stop Being Used to Sell a Future that Doesn’t Serve Us https://disabilityvisibilityproject.com/2023/12/02/robotaxis-wont-get-us-there-so-lets-stop-being-used-to-sell-a-future-that-doesnt-serve-us/

Segregation by Design https://www.segregationbydesign.com/

cars.destroyed.our.cities https://www.instagram.com/cars.destroyed.our.cities/

Bamberg merchants, city officials say downtown open for business https://thetandd.com/news/bamberg-merchants-city-officials-say-downtown-open-for-business/article_fec5d451-61bd-5fe2-904c-bdfecdb19392.html

Historical photos of Utrecht https://hetutrechtsarchief.nl/

Historical photos of Fake London https://search.ourontario.ca/ https://images.ourontario.ca/london/search

De Markt in gebruik als parkeerplaats voor auto's. https://hdl.handle.net/21.12115/NL-DtAD211303220

The number of references far exceeds the maximum length that YouTube allows in descriptions, but you can access the full list of references on Nebula or at this link: https://notjustbikes.com/references/selfdrivingcars.txt

This video was made with video filmed on location by Not Just Bikes, stock footage from Getty Images, and specialty scenes filmed by videographers who were hired for this project. The 3D scenes were created by a professional 3D artist.

No generative AI or AI voices were used in the making of this video

--- Chapters

0:00 Intro 1:17 Reasons for optimism & skepticism 2:33 Moving fast and breaking people 8:50 Fatal Uber Crash 10:34 The Real Road Safety Issue 14:27 Promoting car-centric cities 17:03 Cheaper taxis (yay?) 21:07 Traffic congestion will be even worse 25:19 The promised future (past and present) 28:04 How AVs will destroy cities 29:56 Eliminating public transit 32:37 Consuming all streets 34:02 Eliminating pedestrians 36:05 Eliminating speed limits 38:05 Pollution and noise 39:41 Eliminating traffic lights 42:16 Do we actually need AVs? 43:28 Utrecht vs Fake London 48:33 What should we do about it? 51:53 Where to learn more & Nebula

[Source](https://www.youtube.com/watch?v=040ejWnFkj0)