Machine Learning to Help Optimize Traffic and Reduce Pollution

CS Prof. Alexandre Bayen, the director of the Institute of Transportation Studies,  is leading a traffic-smoothing project dubbed CIRCLES (Congestion Impact Reduction via CAV-in-the-loop Lagrangian Energy Smoothing) that applies deep reinforcement learning to self-driving cars to smooth traffic, reduce fuel consumption, and improve air quality.  The potential for cities is enormous,” said Bayen. “Experiments have shown that the energy savings with just a small percentage of vehicles on the road being autonomous can be huge. And we can improve it even further with our algorithms.”