Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching
Lu Zhang,Wenchao Ding,Jing Chen,Shaojie Shen,Lu Zhang,Wenchao Ding,Jing Chen,Shaojie Shen
Decision-making in dense traffic scenarios is challenging for automated vehicles (AVs) due to potentially stochastic behaviors of other traffic participants and perception uncertainties (e.g., tracking noise and prediction errors, etc.). Although the partially observable Markov decision process (POMDP) provides a systematic way to incorporate these uncertainties, it quickly becomes computationally...
