Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation
Maximilian Igl,Daewoo Kim,Alex Kuefler,Paul Mougin,Punit Shah,Kyriacos Shiarlis,Dragomir Anguelov,Mark Palatucci,Brandyn White,Shimon Whiteson,Maximilian Igl,Daewoo Kim,Alex Kuefler,Paul Mougin,Punit Shah,Kyriacos Shiarlis,Dragomir Anguelov,Mark Palatucci,Brandyn White,Shimon Whiteson
Simulation is a crucial tool for accelerating the development of autonomous vehicles. Making simulation realistic requires models of the human road users who interact with such cars. Such models can be obtained by applying learning from demonstration (LfD) to trajectories observed by cars already on the road. However, existing LfD methods are typically insufficient, yielding policies that frequent...
