3 accepted papers
For autonomous vehicles, effective behavior planning is crucial to ensure safety of the ego car. In many urban scenarios, it is hard to create sufficiently general heuristic rules, especially for challenging scenarios that some new human drivers find difficult. In this work, we propose a behavior pl…
Behavioral decision making is an important aspect of autonomous vehicles (AV). In this work, we propose a behavior planning structure based on hierarchical reinforcement learning (HRL) which is capable of performing autonomous vehicle planning tasks in simulated environments with multiple sub-goals.…
How autonomous vehicles and human drivers share public transportation systems is an important problem, as fully automatic transportation environments are still a long way off. Understanding human drivers’ behavior can be beneficial for autonomous vehicle decision making and planning, especially when…