Integrated Decision Making and Trajectory Planning for Autonomous Driving Under Multimodal Uncertainties: A Bayesian Game Approach

Understand

Modeling the interaction between traffic agents is a key issue in designing safe and non-conservative maneuvers in autonomous driving.

• This problem can be challenging when multi-modality and behavioral uncertainties are engaged.
• Existing methods either fail to plan interactively or consider unimodal behaviors that could lead to catastrophic results.
• In this paper, we introduce an integrated decision-making and trajectory planning framework based on Bayesian game (i.e., game of incomplete information).