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Only ten percent of cars would need to use the algorithm in order to help congestion.

Traffic is, in many ways, a fascinating experiment in human behavior, and a way to observe the consequences of individual acts on the collective. If you’ve ever been driving on the highway and encountered sudden, unexplained traffic which appeared suddenly and then disappeared just as suddenly after a few minutes, then you’ve seen this first hand. A single bad merge or improper braking can send a cascade of traffic out from behind it, and affect everyone on the road. Unfortunately, you cannot turn people into robots; there will always be drivers who either make mistakes, or who greedily take advantage of the road at a cost to other drivers.

This is one of the many advantages of driverless cars. If an impartial, well-trained computer is controlling the vehicle, as opposed to a human, then it may have an easier time optimizing space between vehicles, traffic flow, and more, and could help alleviate traffic jams at least to some degree. Computer scientists at Nanyang Technological University in Singapore have been working on this very issue, and have developed a new intelligent routing algorithm, which they hope will minimize the random unexplained traffic jams mentioned above. Their findings will be published in the April issue of IEEE Transactions on Emerging Topics in Computational Intelligence.

The Nanyang researchers’ algorithm is a type of route-finding algorithm. Route finding is a natural branch of computer science and has been a part of graph theory since before electronic computers even existed. The new traffic algorithm begins by assuming that traffic is going to become congested (experience a “breakdown”) no matter what. The algorithm then attempts to direct the cars in such a way that the effect has minimum possible impact.

“We assume that the traffic breakdown model has already been given, and the probability of traffic breakdown occurrence is larger than zero (meaning that traffic breakdowns would occur), and our goal is to direct the traffic flow so that the overall traffic breakdown probability is minimized,” wrote researcher Hongliang Guo and his colleagues.

According to the researchers, as little as ten percent of cars would have to use their model for even the worst traffic situations to begin seeing improvement. This is interesting news indeed: Autonomous vehicles are becoming more popular, but it’ll be a long time until enough self driving cars are on the road that a majority of them could use a route-finding algorithm. If only a few of them can have a positive effect, perhaps Guo and his team will be able to improve our daily commute sooner rather than later.

source: IEEE