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# Algorithm predicts which cars are most likely to run red lights

Algorithm predicts which cars are most likely to run red lights
MIT has developed an algorithm that predicts which cars are likely to run a red light, so that other drivers can be warned
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MIT has developed an algorithm that predicts which cars are likely to run a red light, so that other drivers can be warned

According to the U.S. National Highway Traffic Safety Administration, for the year 2008, over 700 fatalities resulted from drivers running red lights at intersections across the United States. Approximately half of the people killed weren't the errant drivers themselves, but were other drivers, passengers or pedestrians who simply happened to be in the wrong place at the wrong time. One approach to reducing these numbers is to utilize technology such as Mercedes Benz's Smart Stop system, that won't let drivers run red lights. Scientists at MIT are looking at the problem from another angle, however - they have developed a system that identifies cars likely to run the reds, so that the other drivers can be warned to stay out of their way.

The system uses cameras to view vehicles heading towards an intersection, then applies a custom algorithm to parameters such as their rate of deceleration, and distance from the light. That algorithm was tested using data previously gathered at a busy intersection in Christianburg, Virginia. Out of over 15,000 approaching vehicles within the data-set, the system correctly predicted which ones would run red lights with 85 percent accuracy.

The system was particularly accurate within a window of one to two seconds before a collision could potentially occur. While that might seem like the equivalent of forecasting rain right as the dark clouds are rolling in, the researchers believe that even those couple of seconds would provide a sufficient warning time for other drivers approaching the intersection.

That warning would likely take the form of an alert on a vehicle-to-vehicle communication system, sent by the offending car to all of those in its vicinity.

While the MIT system is not the first of its kind, it is reportedly 15 to 20 percent more accurate than any that have come before it. In particular, it raises fewer false alarms, which would make it less annoying for drivers to use.

The research team is now looking into getting the system not just to alert motorists to the presence of red-light-runners, but to suggest evasive actions. There are also plans to adapt the algorithm for use in air traffic control, where it would predict what aircraft were likely to do.