Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections. (arXiv:2201.07833v1 [eess.SY])

Taking advantage of both vehicle-to-everything (V2X) communication and
automated driving technology, connected and automated vehicles are quickly
becoming one of the transformative solutions to many transportation problems.
However, in a mixed traffic environment at signalized intersections, it is
still a challenging task to improve overall throughput and energy efficiency
considering the complexity and uncertainty in the traffic system. In this
study, we proposed a hybrid reinforcement learning (HRL) framework which
combines the rule-based strategy and the deep reinforcement learning (deep …

arxiv hybrid learning reinforcement learning strategy