Comprehensive Automated Driving Maneuvers under a Non-Signalized Intersection Adopting Deep Reinforcement Learning
Automated driving systems have become a potential approach to mitigating collisions, emissions, and human errors in mixed-traffic environments.This study proposes the use of a deep reinforcement learning method to verify the effects of comprehensive automated vehicle movements at a non-signalized intersection according to training policy and measur