Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety

Overview

The framework learns urban driving policies from offline connected-driving data through imitation learning. An integrated safety controller constrains behavior at test time, with evaluation conducted in realistic urban-driving simulations.