Study: Hacking 10 percent of self-driving cars would cause gridlock in NYC
Enlarge / A traffic jam in New York City. (credit: Johannes Eisele/AFP/Getty Images)
In 2015, a pair of hackers demonstrated just how easy it was to break into the UConnect system of a Jeep Cherokee, remotely manipulating the speed, braking, steering, even shutting the car down entirely. Vehicles on the road will only have greater interconnectivity from this point forward, with self-driving cars on the horizon. That poses a unique potential risk: if someone can hack one car, what happens if they manage to hack many at once in a major metropolitan city?
That question inspired scientists at the Georgia Institute of Technology to quantify the likely impact of such a large-scale hack on traffic flow in New York City. Skanda Vivek, a postdoctoral researcher at Georgia Tech, described the study's findings at the American Physical Society's 2019 March meeting, held last week in Boston. Worst-case scenario: a small-scale hack affecting just ten percent of cars on the road would be sufficient to cause city-wide gridlock, essentially cutting half of Manhattan off from the rest of the city. And unlike compromised data, compromised vehicles can lead to physical injury.
Vivek and his colleagues performed computer simulations of traffic flow in Manhattan, using a statistical method called percolation theory. If that reminds you of brewing coffee, that's exactly the right image. Percolation theory is a mathematical model of a smooth, continuous phase transition (as opposed to a rapid one, like flicking a light switch), similar to water seeping through roasted ground coffee beans until it shifts into a new state: "coffee." Hot water seeping through packed coffee grains will hunt for the most viable path. The more connected routes that are open, the more likely it is the water will filter through. Traffic works much the same way. Cut off too many routes, and there won't be sufficient connectivity for cars to filter through.
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