Diverse Critical Interaction Generation for Planning and Planner Evaluation
Zhao-Heng Yin,Lingfeng Sun,Liting Sun,Masayoshi Tomizuka,Wei Zhan,Zhao-Heng Yin,Lingfeng Sun,Liting Sun,Masayoshi Tomizuka,Wei Zhan
Generating diverse and comprehensive interacting agents to evaluate the decision-making modules is essential for the safe and robust planning of autonomous vehicles (AV). Due to efficiency and safety concerns, most researchers choose to train interactive adversary (competitive or weakly competitive) agents in simulators and generate test cases to interact with evaluated AVs. However, most existing...
