Hybrid Reinforcement Learning-Based Eco-Driving Strategy for Connected and Automated Vehicles at Signalized Intersections

no code implementations • 19 Jan 2022 • Zhengwei Bai, Peng Hao, Wei Shangguan, Baigen Cai, Matthew J. Barth

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.

reinforcement-learning Reinforcement Learning (RL) +1

Deep Learning Based Motion Planning For Autonomous Vehicle Using Spatiotemporal LSTM Network

no code implementations • 5 Mar 2019 • Zhengwei Bai, Baigen Cai, Wei Shangguan, Linguo Chai

In this paper, we proposed a motion planning model based on deep learning (named as spatiotemporal LSTM network), which is able to generate a real-time reflection based on spatiotemporal information extraction.

Motion Planning

Deep Reinforcement Learning Based High-level Driving Behavior Decision-making Model in Heterogeneous Traffic

no code implementations • 15 Feb 2019 • Zhengwei Bai, Baigen Cai, Wei Shangguan, Linguo Chai

In this paper, a deep reinforcement learning based high-level driving behavior decision-making approach is proposed for connected vehicle in heterogeneous traffic situations.

Decision Making reinforcement-learning +1