Researchers Say Smart Intersections & Autonomous Cars Could Reduce Urban Congestion
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It has happened to all of us. We are driving along in the city at a nice steady 30 miles per hour when suddenly the traffic light ahead turns red. Traffic comes to a halt. The flow has been broken. Why can’t someone coordinate all the traffic lights to make traffic flow better and help get rid of some of this congestion?
Some people learn to game the system. My old Irish grandfather — as stubborn and cantankerous a man as you are ever likely to find — figured out that if he drove exactly 17.5 mph in his neighborhood, he would get every light green. Other cars would roar by, with horns blaring. Often the other drivers took to gesticulating wildly with their hands and fingers. A few minutes later, they would be stopped at a light as my grandfather glided by just as the light turned green, making them pass him all over again. It was a game that gave him much pleasure, but it was no fun to ride along with him.
Researchers at Cornell say new connected technologies would allow traffic signals and autonomous cars to talk with each other, allowing traffic to flow more smoothly and reducing congestion, according to a report in Science Daily. Their research, entitled “Optimal traffic control at smart intersections: Automated network fundamental diagram,” has been published by the journal Transportation Research.
“For the future of mobility, so much attention has been paid to autonomous cars,” says Oliver Gao, professor of civil and environmental engineering and senior author of the study. “If you have all these autonomous cars on the road, you’ll see that our roads and our intersections could become the limiting factor. In this paper we look at the interaction between autonomous cars and our infrastructure on the ground so we can unlock the real capacity of autonomous transportation.”
The researchers created a model that allows groups of autonomous cars, known as platoons, to pass through one-way intersections without waiting. The research showed the model increased the capacity of vehicles on city streets up to 138% compared to a conventional traffic signal system. The model assumed only autonomous cars are on the road. The team is now expanding its research to model what happens when autonomous and conventional cars share the same street.
Autonomous vehicles will be able to communicate with each other, the researchers say, which will introduce opportunities for coordination and efficiency. That coordination could include interaction with smart traffic control systems in order to optimize traffic flow, allowing cars to pass quickly and safely through intersections. “Instead of having a fixed green or red light at the intersection, these cycles can be adjusted dynamically,” Gao said. “And this control can be adjusted to allow for platoons of cars to pass.”
So far, ride-hailing services seem to be increasing urban congestion rather than decreasing it. Perhaps removing human drivers from the ride-hailing model and turning control over to computers running advanced algorithms as suggested by the Cornell research could be the answer to finally reducing the headache of clogged city streets.
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