“It’s a missed opportunity,” says Robin Chase, a transportation entrepreneur best known for cofounding Zipcar. “The transponder in your car is a device that’s used 30 seconds in a month and is a 20-year-old technology.” She suggests the MTA rely on smartphones to make drivers pay for road use. She says the MTA should work with third-party providers to use location data and charge drivers based on how much they drive. It’s as if Waze came with a payment system. Or if Uber’s surge-pricing algorithm, location-tracking feature, and payment interface were applied to all vehicles.
While the idea of having one’s location tracked at all times may raise privacy concerns, Chase says adding more cameras on the street is far more worrisome. (EZ Pass uses cameras to pull the license plates of cars without transponders and mails their owners a bill.) “Putting in the physical infrastructure that creates [a] surveillance state is deeply troubling right now, particularly as we start talking about facial recognition,” she says.
The state of New York is already running its own pilot project to test facial-recognition cameras at toll bridges and tunnels. While the MTA has denied the data would be shared with law enforcement officials, civil liberties advocates have warned that such technology only serves to increase the government’s capacity for real-time surveillance. “There’s lots of examples where cameras were installed for a particular use and then immediately reused for other uses,” Chase warns.
When asked whether the new congestion system will incorporate smartphone-based technologies, an MTA spokesperson wrote in an email: “We are committed to bringing innovative solutions and the world’s best technology to this project and are exploring a wide range of both traditional and outside-of-the-box solutions.”
Others agree the E-ZPass lacks flexibility but think relying on smartphone technology alone may not be sufficient. Paul Salama, the chief operating officer at ClearRoad, a road-pricing company, notes that GPS struggles in dense urban environments, which explains why sometimes you don’t see your Uber moving in real time on your phone’s screen. And there would need to be a way to associate a phone with a specific vehicle, to make sure that the person being charged is actually the one driving.
ClearRoad currently works with the states of Oregon and Washington to implement per-mile pricing programs. Those were launched when both states took steps to replace existing fuel taxes, revenues from which are threatened by the rise of electric cars. ClearRoad’s platform collects data on road use from a variety of sources, including built-in navigation systems and transponders, and applies whatever pricing policy the government has put into place, acting like a data broker.
Salama says his platform also protects the privacy of drivers, because it mostly works with anonymized data and doesn’t handle payments itself. “Governments actually don’t want this data. They don’t want to worry about how they manage this data. So we prevent them from having anything aside from aggregate data,” he says.
To get a better idea of what a fully fledged data-based congestion pricing scheme would look like, you can skim through the April proposal made by the Centre for London for the city’s soon-to-be-updated road-pricing plan. It suggests charging drivers based on distance traveled, vehicle emissions, real-time congestion, and availability of public transit. Drivers would have the choice to be tracked via their smartphone or by a transponder-like device. Visitors and those who wish to opt out due to privacy concerns could purchase prepaid credits online or in physical stores.
And the proposal says London should create an app through which users could not only pay for road charges, but also plan their trips and compare different modes of transportation based on travel time and road pricing. In short, it would merge the features of a mobility-as-a-service app (such as Whim in Helsinki) with the location-tracking and billing system of a ride-hailing service.