MIT computer predicts red-light runners

Dec. 2, 2011

Researchers at MIT have created a computer algorithm that predicts when an oncoming car is likely to run a red light, the MIT News Office reported. The goal is to prevent some of the 2.3 million (according to NHTSA) automobile crashes that occur at intersections in a year in the U.S.

 

Based on parameters such as the vehicle’s deceleration and its distance from a light, the researchers were able to determine which cars were potential “violators” (i.e., likely to cross into an intersection after a light has turned red) and which were likely to be “compliant.”

Researchers at MIT have created a computer algorithm that predicts when an oncoming car is likely to run a red light, the MIT News Office reported. The goal is to prevent some of the 2.3 million (according to NHTSA) automobile crashes that occur at intersections in a year in the U.S.

Based on parameters such as the vehicle’s deceleration and its distance from a light, the researchers were able to determine which cars were potential “violators” (i.e., likely to cross into an intersection after a light has turned red) and which were likely to be “compliant.”

The researchers tested the algorithm on data collected from an intersection in Virginia, finding that it accurately identified potential violators within a couple of seconds of reaching a red light—enough time, according to the researchers, for other drivers at an intersection to be able to react to the threat if alerted. Compared with other efforts to model driving behavior, the MIT algorithm generated fewer false alarms, an important advantage for systems providing guidance to human drivers.

The researchers report their findings in a paper that will appear in the journal IEEE Transactions on Intelligent Transportation Systems.

“If you had some type of heads-up display for the driver, it might be something where the algorithms are analyzing and saying, ‘We’re concerned,’” said Jonathan How, the Richard Cockburn Maclaurin Professor of Aeronautics and Astronautics at MIT, who is one of the paper’s authors. “Even though your light might be green, it may recommend you not go, because there are people behaving badly that you may not be aware of.”

How said that in order to implement such warning systems, vehicles would need to be able to “talk” with each other, wirelessly sending and receiving information such as a car’s speed and position data. Such vehicle-to-vehicle (V2V) communication, he says, can potentially improve safety and avoid traffic congestion. Today, the U.S. Department of Transportation (DOT) is exploring V2V technology, along with several major car manufacturers, including Ford Motor Co., which this year has been road-testing prototypes with advanced Wi-Fi and collision-avoidance systems.

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