Monday, July 10, 2017

How An MIT Simulation Game Uses Deep Learning to Reduce Gridlock

Being stuck in traffic is frustrating and expensive. Beyond headaches and missed appointments, traffic congestion costs U.S. drivers some $300 billion annually. Researchers suggest self-driving cars — even in small numbers — will dramatically improve traffic flow. Lex Fridman and his team at MIT created a game to accelerate this future. DeepTraffic simulates a typical highway environment, and its players control their own car using deep learning. The simulation makes complex technical concepts accessible for beginners, and the gamification pushes experts to develop completely new techniques.