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Jeudi, 01 Décembre 2011 15:00

Model Predicts Who Will Run Red Lights

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Model Predicts Who Will Run Red Lights

MIT researchers have developed an algorithm that can predict whether a car is about to run a red light, a calculation they estimate could prevent millions of crashes and 700 deaths each year if paired with vehicle-to-vehicle (V2V) communication.

Using data collected from DOT-sponsored surveillance of a busy intersection in Christianburg, Virginia to track vehicle speed and location, the researchers could determine, within two seconds of a car approaching an intersection, with 85 percent accuracy whether it would run a red light.

They’ve tested their algorithm on more than 15,000 cars and found it is a vast improvement over current models, which are only 15 to 20 percent accurate.

As interesting as predictive models can be, they’re useless to drivers unless they’re integrated into some sort of warning system. That’s where vehicle-to-vehicle communication technology comes in. Cars that communicate with each other over a local WiFi network can alert drivers approaching an intersection and warn them that it might not be safe to proceed.

“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,” said Jonathan How, an aeronautics and astronautics professor who co-created the algorithm.

According to How, consumers may find a intersection collision avoidance feature attractive enough to buy cars equipped with V2V technology. As more and more cars communicate with each other, the technology becomes increasingly valuable.

“You might have a situation where you get a snowball effect where, much more rapidly than people envisioned, this [V2V] technology may be accepted,” he said.

That scenario only applies if the alarm is well-integrated, though, as consumers will dismiss any warnings they deem irrelevant. The algorithm’s creators found that sounding a warning between one and two seconds of a potential collision gives drivers enough time to react without being overly cautious.

“If you’re too pessimistic, you start reporting there’s a problem when there really isn’t, and then very rapidly, the human’s going to push a button that turns this thing off,” How said.

Photo: Flickr/midweekpost


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