Connectedness
The ability to drive itself, or automation, is clearly a critical feature of an autonomous vehicle. But the other critical feature is its connectedness to other vehicles and their surroundings, including pedestrians, infrastructure, and the network, which allows for the optimization of the vehicular system as a whole. Connectedness is achieved by various communication models, summarized by Mutschler (2018) as follows:
vehicle to infrastructure (V2I), which includes communications to traffic-signal timing, speeds limits, prioritization, and traffic signs (for example, changing traffic signal lights)
vehicle to vehicle (V2V), which enables collision avoidance (for example, ambulance approaching)
vehicle to pedestrian (V2P), which can transmit safety alerts to pedestrians and cyclists (for example, vehicle approaching, pedestrian crossing street ahead)
vehicle to network (V2N), which enables communication about real time traffic, work zones, routing, and cloud services (for example, traffic congestion two miles ahead)
Policymakers must engage with the autonomous-vehicle industry to determine the appropriate investments that could enable autonomous vehicles to operate safely and efficiently in their states and cities with the essential communication capabilities.
Incentives for Automakers and Technology Companies
Chris Urmson, the former director of self-driving cars at Google, argues that the private sector has a financial incentive to expedite deployment of autonomous vehicles because it can earn revenues on a per mile rather than a per unit basis. He refers to the following equation to approximate the size of the industry based on revenue:
3 trillion VMT × $0.10 per mile = $300 billion per year,
where VMT refers to annual vehicle miles traveled in the United States and travelers are charged $0.10 a mile to cover costs.
Bosch and others (2018) finds a somewhat higher cost figure, based on a review of academic empirical estimates of the cost per mile of autonomous vehicles that puts the cost in the range of $0.15–$0.20 per mile. In any case, Urmson offers a plausible hypothesis that travelers could reduce the capital costs of vehicle ownership, including insurance, by apportioning them over the number of miles driven by acquiring or sharing a vehicle through a “transportation subscription service.”8
Automakers could then improve their earnings by selling the use of autonomous vehicles that consumers share through rentals or subscriptions instead of by selling a given volume of units. Individuals and households would operate autonomous vehicles as transportation as a service (TaaS).9 For example, assuming, on average, that auto companies currently turn a profit of roughly $1,500 per car and that a car lasts 150,000 miles, then their profit is a penny per mile traveled, which is likely to be less than the profit per mile traveled that they could earn by charging consumers a per mile fee for a shared autonomous vehicle.10 Of course, the extensive collaboration in the autonomous-vehicle industry, the reinvention that autonomous-vehicle providers will have to make in the way they market and differentiate services, and firms’ extensive investments in R&D and their huge fixed costs suggest a high degree of uncertainty about the level and distribution of future profits.
Travelers’ Incentives for Adoption
Adopting autonomous vehicles would also greatly benefit travelers. Small and Verhoef (2007) reports that the average cost of highway travel time and unreliability amounts to $0.40 per mile and that the average cost of accidents is $0.14 per mile. If travelers pay $0.10 per mile, or even somewhat more, for their autonomous-vehicle transportation, those costs are likely to be strongly offset by the benefits from reduced travel times and greater reliability and from the virtual elimination of accident costs.
The large benefits from this back-of-the-envelope calculation are consistent with Fagnant and Kockelman (2015), which accounts for the benefits from the reduction in vehicle accidents and travel delays under the assumption that autonomous vehicles would reduce freeway delays from 35 to 60 percent, depending on the extent of autonomous vehicle (AV) market penetration and accounting for the additional travel that the vehicles may induce that would increase congestion.11
Technologically, the large benefits accrued from reducing congestion derive from the basic relation, traffic flow = travel speed × traffic density. Consider the case of a traffic accident that creates significant congestion, as people rubber neck to view the incident, causing traffic to slow to a crawl. Autonomous vehicles could significantly increase travel flows in such situations because they could smooth traffic flow and travel closer together without jeopardizing safety and could maintain a more consistent speed by not slowing down to view the aftermath. As noted, incident delays account for roughly one-third of all delays, so even modest improvements in traffic flows from reducing those delays could amount to significant savings in time and reliability that could yield large social benefits. Of course, autonomous vehicles could also improve traffic flows by the same type of mechanism to reduce other types of delays.
Wu and others (2017) presents simulations to examine the impact that autonomous vehicles could have on improving traffic flows even in traffic that includes nonautonomous vehicles. Small experiments involving a few dozen cars on a closed circuit show that a single autonomous vehicle could reduce traffic congestion by subtly moderating the speed of every other car on the road. In larger simulations, once autonomous vehicles reach a level of 5 to 10 percent of all cars on the road, they can manage localized traffic in complex environments—such as when eight lanes of traffic merge into two or at an extremely busy intersection. An autonomous vehicle carefully increases the space between itself and the car ahead, anticipating that it will abruptly slow down at some point down the road. However, because the self-driving vehicle has created a buffer, it can keep driving at the same pace—avoiding the cascade effect that its own braking would have on the cars behind it. In time, a new equilibrium is reached where all the cars are moving at a steady pace.
Daziano, Sarrias, and Leard (2017) takes a different perspective on travelers’ benefits from autonomous vehicles and finds that the average household’s willingness to pay for those vehicles greatly exceeds the additional cost of the technology. To be sure, our rough calculation and the preceding studies should be qualified because the actual benefits of autonomous vehicles will depend on whether the government reforms policies that would enhance their driving environment and performance. They will also be affected by the extent to which travelers reduce the capital costs of vehicle ownership by sharing vehicles through transportation subscription services.
The Role of the Government
Applying autonomous-vehicle prototypes to multiple geographies is difficult because cities have different road infrastructures—from signs to road paint—and different norms that drivers follow. In addition, no public benchmarks exist for how autonomous vehicles should perform in a given scenario to meet a standard of safety. Accordingly, all levels of government have a critical role to play in the public’s adoption of autonomous vehicles because the public highway infrastructure is provided by local, state, and federal governments and because the federal government is generally responsible for regulating motor-vehicle safety.
Other major innovations have also relied on infrastructure provided by the government. For example, cell phones and eventually smartphones relied on the government-provided electromagnetic spectrum to enable communication through cellular technology. Similarly, autonomous vehicles must depend on the public road system to transport passengers and freight by vehicles that drive themselves. Because inefficient infrastructure policies have contributed to the large social costs of nonautonomous vehicle travel, it is important for policymakers to reform highway-infrastructure