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

Researchers deployed 100 reinforcement learning-controlled cars into rush-hour highway traffic to smooth congestion and reduce fuel consumption. The RL agents learned to maximize energy efficiency while maintaining throughput and operating safely around human drivers. The controllers rely on standard radar sensors and operate in a decentralized manner.