Simulating the Future of Traffic with RL w/ Cathy Wu - #362

Cathy Wu, an MIT Assistant Professor, dives into her groundbreaking work using reinforcement learning to tackle mixed autonomy traffic challenges. She shares insights from her simulations of various traffic scenarios—like intersections and merges—revealing how autonomous vehicles can improve overall traffic efficiency. Wu emphasizes the surprising benefits even a few automated cars can have in reducing wait times and enhancing flow. Their interactions with human drivers and the implications for urban planning are also explored, sparking thought on the future of transportation.