Expert Paints Picture of an Autonomous Robot-Fuelled Gridlock

A UC Santa Cruz professor suggests self-driving cars will torpedo parking pricing as effective congestion management policy; “incentive to create havoc”

Autonomous vehicles are set to become a reality sooner or later. However, one aspect with regards to autonomous vehicular traffic seems to have been overlooked till date. Autonomous vehicles (AVs) could clog city streets and slow traffic to a crawl according to a research done by Adam Millard-Ball, an associate professor of environmental studies at UC Santa Cruz, according to reports by Jennifer McNulty at UC Santa Cruz.

Millard-Ball anticipates a scenario of robot-fuelled gridlock right around the corner given that autonomous, or self-driving, vehicles are likely to become commonplace in the next five to 20 years. Millard-Ball is the first researcher to analyze the combined impact of parking costs and self-driving cars on city centers. Millard-Ball points out that, “Parking prices are what get people out of their cars and on to public transit, but autonomous vehicles have no need to park at all. They can get around paying for parking by cruising. They will have every incentive to create havoc.”

An excerpt from his paper published in the journal Transport Policy states:

‘In this paper, I identify and analyze a new channel through which AVs will have unambiguously negative environmental consequences—the removal of parking pricing, one of the most effective congestion management policies, from the urban transportation policy toolbox. AVs not only can avoid parking charges through cruising (that is, circling around while waiting for a passenger), but also have the incentive to seek out and exacerbate congestion—even gridlock—in order to minimize costs to their owners.

… This paper suggests that the parking behaviour of autonomous vehicles would land cities with a twofold blow—a dramatic drop in the cost of parking that encourages more trips by car, and greater vehicle travel and congestion from each trip due to cruising, returning home, and travelling to free on-street spaces. The reduced price of parking would likely increase vehicle travel to dense, urban cores by 98%, while cruising and travel to and from remote parking spaces would add a further 8%.

Millard-Ball predicts that under the best-case scenario, the presence of as few as 2,000 self-driving cars in downtown San Francisco will slow traffic to less than 2 mph. Economists and environmentalists agree that congestion pricing effectively reduces congestion and pollution and Millard-Ball sees an opportunity here. He proposes congestion pricing—which essentially amounts to a user fee—as a solution. In London, motorists pay a flat fee to enter the city center. Singapore and Stockholm employ similar models. More sophisticated models could charge by miles driven, or assign different fees to particular streets.

Hourly cost of work parking. Source: Data from San Francisco County Transportation Authority

Millard-Ball suggests that self-driving cars be outfitted with devices that would give policymakers options for levying fees based on location, speed, time of day—even which lane the vehicle occupies. The fees could raise money for cities to improve transportation. The idea is to do it now before autonomous vehicles become widespread he emphasises.