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.
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.