DeepTraffic – MIT simulator for autonomous driving
DeepTraffic (https://selfdrivingcars.mit.edu/deeptraffic/) was created for the course MIT 6.S094: Deep Learning for Self-Driving Cars at MIT taught by Lex Fridman. Course content and assignment is public. DeepTraffic gained a lot of popularity owing to its leaderboard. With over 13,000 submissions to date, DeepTraffic is highly competitive. The users have to write their neural networks in convnet.js (a framework created by Andrej Karpathy) in the coding ground present in the link mentioned at the start of the section. The agent with the maximum average speed tops the leaderboard.
Simulations such as DeepTraffic help train different approaches to make the car agent adapt to the simulated environment quickly. Moreover, the competitive element of it adds to better submissions over time, beating the past top scores. The competition makes it fun but in the real world a student can't test their deep reinforcement learning scripts. Therefore, DeepTraffic...
