Scaling Up Reinforcement Learning for Traffic Smoothing: A 100-AV Highway Deployment

Researchers deployed 100 RL-controlled cars to smooth congestion and reduce fuel consumption on highways. These AVs learned to mitigate stop-and-go traffic waves through data-driven simulations and real-world tests, achieving significant energy savings. The field test demonstrated the scalability and potential of this approach to improve traffic flow and efficiency with minimal infrastructure changes.