Transportation AI ‘Uber Was Supposed to Help Traffic. It Didn’t. Robotaxis Will Be Even Worse.’
Saturday the San Francisco Chronicle published a joint opinion piece from MIT professor Carlo Ratti (who directs an MIT digital lab exploring the collection of digital data about urban life) and John Rossant (founder of the collaborative data-sharing platform CoMotion).
Together they penned a warning about a future filled with robotaxis. “Their convenience could seduce us into vastly overusing our cars. The result? An artificial-intelligence-powered nightmare of traffic, technically perfect but awful for our cities.”
Why do we believe this? Because it has already come to pass with ride-sharing. In the 2010s, the Senseable City Lab at the Massachusetts Institute of Technology, where one of us serves as the director, was at the forefront of using Big Data to study how ride-hailing and ride-sharing could make our streets cleaner and more efficient. The findings appeared to be astonishing: With minimal delays to passengers, we could match riders and reduce the size of New York City taxi fleets by 40%. More people could get around in fewer cars for less money. We could reduce car ownership, and free up curbs and parking lots for new uses. This utopian vision was not only compelling but within reach.
After publishing our results, we started the first collaboration between MIT and Uber to research a then-new product: Uber Pool (now rebranded UberX Share), a service that allows riders to share cars when heading to similar destinations for a lower cost. Alas, there is no such thing as a free lunch. Our research was technically right, but we had not taken into account changes in human behavior. Cars are more convenient and comfortable than walking, buses and subways — and that is why they are so popular. Make them even cheaper through ride-sharing and people are coaxed away from those other forms of transit. This dynamic became clear in the data a few years later: On average, ride-hailing trips generated far more traffic and 69% more carbon dioxide than the trips they displaced. We were proud of our contribution to ride-sharing but dismayed to see the results of a 2018 study that found that Uber Pool was so cheap it increased overall city travel: For every mile of personal driving it removed, it added 2.6 miles of people who otherwise would have taken another mode of transportation.
As robotaxis are on the cusp of proliferating across the world, we are about to repeat the same mistake, but at a far greater scale… [W]e cannot let a shiny new piece of technology drive us into an epic traffic jam of our own making. The best way to make urban mobility accessible, efficient and green is not about new technologies — neither self-driving cars nor electric ones — but old ones. Buses, subways, bikes and our own two feet are cleaner, cheaper and more efficient than anything Silicon Valley has dreamt up… Autonomous technology could, for example, allow cities to offer more buses, shuttles and other forms of public transit around the clock. That’s because the availability of on-demand AVs could assure “last-mile” connections between homes and transit stops. It could also be a godsend for older people and those with disabilities. However, any scale-up of AVs should be counterbalanced with investments in mass transit and improvements in walkability.
Above all, we must put in place smart regulatory and tax regimes that allow all sustainable mobility modes — including autonomous services — to scale safely and intelligently. They should include, for example, congestion fees to discourage overuse of individual vehicles.