Driving requires reacting to a wide variety of complex environment conditions and agent behaviors.
Ranked #13 on Autonomous Driving on CARLA Leaderboard
We propose a convolutional recurrent neural network, with Winner-Take-All dropout for high dimensional unsupervised feature learning in multi-dimensional time series.
Comma. ai's approach to Artificial Intelligence for self-driving cars is based on an agent that learns to clone driver behaviors and plans maneuvers by simulating future events in the road.