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Summary:

An MIT professor has created an algorithm he says can work in conjunction with rangefinders and adaptive cruise control systems to keep cars moving at the ideal speeds to limit traffic jams.

If there’s a part of day-to-day living that leaves me feeling more helpless than a traffic jam, I don’t know what it is. I mean, everyone is heading in the same direction, so why the heck am I stopping every one-eighth mile or, worse yet, stuck in this same darn spot for the past five minutes?!

Thankfully, relief could be on the way thanks to research from MIT professor Berthold Horn, who has created an algorithm that could let cars with adaptive cruise control keep near-perfect pace with the cars around them (you can read the entire research paper here). The technique works by equipping cars with rangefinders and other sensors (which those with adaptive cruise control already have) to gauge the distance and speed of cars ahead of them and behind them. Given this data, an algorithm that Horn developed has proven effective in simulations at leveling out flows in any number of different situations by reducing the kind of sudden braking that ends up starting problems on busy roads.

Source: MIT/Berthold Horn

Traffic backup starts at around 30 seconds, and Horn’s method kicks in at around 1 minute. Source: MIT/Berthold Horn

The one big caveat is that the types of sensors required to gauge speed and distance are expensive and generally relegated to high-end vehicles, and this type of system, like vaccination programs, only works if a sufficient number of cars are participating. And although sensors are getting cheaper by the day, the fact that this type most likely has to be wired to a car’s electronic system (as opposed to a cloud software platform, for example) might mean it will be a few generations of cars before they’re commonplace.

In theory, more (or any) self-driving cars on the road could help this technique become more effective, too. They’re loaded with sensors just for this type of speed-and-distance analysis, and one has to think manufacturers will want to make them as smart as possible to ensure they’re more of a help than a hindrance on the road.

For now, though, word of Horn’s work might just leave denizens of Southern California and other major metropolitan areas drooling with anticipation.

Feature image courtesy of Shutterstock user Aaron Kohr.

  1. THIS would make driving soooooo boring, y would anyone want to do it? if this is what driving becomes, i’ll use that transporter technology, please!

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  2. So what part of this algorithm addresses, say a deer, a blowout, a jackknife tractor trailer, chicken cages and chickens loosed by the truck who swerved out of the way to avoid the rolling hubcap that popped off the wheel, and of course, the distracted driver who’s eating or texting? Oh, you don’t have that on the L.A. Freeway? We do.

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  3. Interesting no cars are switching lanes either. Why not simulate what would really happen when you get people trying to fill in the gaps in the lane next to them as their lane jams up and they all switch over to fill in those gaps and then their lane starts moving so they switch back. How does the algorithm handle that phenomena?

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  4. wow this is so amazing
    i like that

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  5. If this works–NOBEL PRIZE FOR PEACE!

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  6. last name Horn. Hilarious.

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  7. Been doing this for years – I call it the ‘keep it moving’… er algorithm. No computers here… I try never to come to a complete stop in heavy traffic – leaving more space in front and adjusting my speed down to very low speed levels to ‘keep it moving’. Just one person doing this helps dozens of cars behind to keep moving, which greatly improves gas mileage, is thus better on the environment and improves overall speed of the traffic. So a much easier solution is to educate people on ‘keeping it moving’. Problem is, as the ‘leader’ of the crew, you have to leave more space in front, and then people always cut in. So the real problem is, people cutting in – an endemic problem in North America compared to other countries.

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