Imagine driving through Los Angeles in the year 2040. There’s a mix of self-driving and human-controlled vehicles on Santa Monica Boulevard. A serious collision slows traffic to a crawl. But then a special orchestration of traffic signals flips on, parting the sea of cars for an ambulance to throttle through the streets.

This traffic engineering fantasy may be inching to reality, as companies such as IBM, Microsoft, Google, and HERE Maps develop what’s known as “digital twin” technology. The term describes a virtual simulacra of something in the physical world—whether it’s a car engine, a casino floor, or the street network of a major city—that visualizes real changes as they occur, and is “smart” enough to model possible scenario outcomes. In the L.A. example, imagine that a downtown city worker viewed a traffic simulation seconds after the car crash and approved a recommended route for the ambulance, alerting all those connected self-driving vehicles to move aside.

The threat of state preemption is enough to give any city official pause. In the first half of 2019, Reynolds decided to transfer the governance of MDS to an outside entity with a more formal decision-making structure than Los Angeles alone. In late June, the Open Mobility Foundation was formally announced, with funding from the Rockefeller Foundation, advisors from the open-source standards group OASIS, and corporate members including Bird, Spin, and Microsoft. (Uber and Lyft weren’t invited to join, Wired reported.) A press release announcing OMF describes a mission “to promote safety, equity and quality of life,” at a time when “the number and type of vehicles using the existing public right-of-way rises dramatically in cities across the country.”

One of the first orders of business at Monday’s OMF board meeting will be to vote on whether to adopt the new bylaws, including the parts about digital twins. “The board can decide to jettison it all,” Reynolds said. But what leaders will be mulling goes far beyond little scooters.

The rise of the digital twin

An early proof of concept for digital twin technology came in 2014. Researchers from the University of Washington announced that they had created “a self-organized and scalable multiple-camera tracking system that tracks humans across the cameras” by pairing Google Street View with a clutch of smart surveillance cameras, trained on city streets. They had demonstrated the possibility of building a close-to-real-time, changing visualization of mobility flows, mapped onto a Google’s panoramic photograph of the world. Machine-learning software rendered any seams invisible.

To date, though, none of these approaches have quite reached the level of direct oversight envisioned in OMF’s bylaws. It takes the current powers of MDS and its various data-exchange programs to a much higher level. A traffic planner of a centralized control system would be alerted to changing conditions in real time, as notified by the real-time streams of data constantly redrawing their digital terrains. Built-in AI would inform an engineer about the best decision to make. OMF offers a couple of examples of how this super-advanced SimCity would run traffic simulations:

As a virtual, ‘living’ equivalent of the city’s many systems, a Digital Twin allows a DOT to model possible strategies to plan for and mitigate problems before and as they occur, and to implement a solution which has been virtually tested in many simulated scenarios to minimize risk. For instance, if a stadium lets out 20,000 patrons at 9:30 pm after a given event, what is the best temporary, one-way street configuration? And for how long should the temporary configuration remain in effect? City planners and operators can use dashboards which provide access to different planes of the physical and virtual worlds to gain the insights needed for effective decision making.

This kind of omniscience is a far cry from the obstructed views of urban movement that some mobility companies now provide to cities. Those are batches of highly aggregated data, such as Uber’s trip data visualization platform, Movement. “These systems represent partial, private and conflicting views of the world that are at odds with the needs and priorities of the city and its residents (and may contradict or attempt to countermand each other as well),” the OMF bylaws state. “Going forward, each city must manage its own Digital Twin, which will provide the ground truth on which mobility services depend.”

Some of this sounds great—a city that’s able to rush ambulances through traffic by rerouting other drivers with a few keystrokes might save lives. Still, some officials and data experts wonder about the excess of individualized information that a digital twin would require a city to own, heightening the privacy concerns that are already clouding MDS. OMF’s bylaws mention some broad privacy principles, but critics—among them, leaders of rival mobility data companies—say that that’s working backwards: Step one should be to hammer out how cities are going to take care of protecting citizen identities, not to keep scaling up their surveillance powers.

“I don’t even understand how that vision is compatible with any notion of privacy,” said William Henderson, the CEO of Ride Report, a startup that worked closely with Los Angeles and other cities to provide mobility data management software. “The vision itself is certainly not the one that we share, and not one that all the cities share.”

Regina Clewlow, the CEO of Populus, a similar software startup that helps cities translate and analyze mobility data, agreed. “Based on our conversations with cities today, we find that many are primarily concerned with having enough detailed data to inform and enforce parking policies, vehicle caps, and equity requirements—not to establish real-time control systems, at least not for scooters,” she said.