A Nash Q-Learning Based Motion Decision Algorithm With Considering Interaction to Traffic Participants. - Can Xu; Wanzhong Zhao; Lin Li 056; Qingyun Chen; Dengming Kuang; Jianhao Zhou (IEEE Trans. Veh. Technol., 2020)

An Improved IOHMM-Based Stochastic Driver Lane-Changing Model. - Qingyun Chen; Wanzhong Zhao; Can Xu; Chunyan Wang 013; Lin Li 056; Shijuan Dai (IEEE Trans. Hum. Mach. Syst., 2021)

Lane-Change Intention Inference Based on RNN for Autonomous Driving on Highways. - Lin Li 056; Wanzhong Zhao; Can Xu; Chunyan Wang 013; Qingyun Chen; Shijuan Dai (IEEE Trans. Veh. Technol., 2021)

ES-DQN: A Learning Method for Vehicle Intelligent Speed Control Strategy Under Uncertain Cut-In Scenario. - Qingyun Chen; Wanzhong Zhao; Lin Li 056; Chunyan Wang 013; Feng Chen (IEEE Trans. Veh. Technol., 2022)

POMDP Motion Planning Algorithm Based on Multi-Modal Driving Intention. - Lin Li 056; Wanzhong Zhao; Chunyan Wang 013 (IEEE Trans. Intell. Veh., 2023)

Eco-Friendly On-Ramp Merging Strategy for Connected and Automated Vehicles in Heterogeneous Traffic. - Jinqiang Liu; Wanzhong Zhao; Chunyan Wang 013; Can Xu; Lin Li 056; Qingyun Chen; Yubo Lian (IEEE Trans. Veh. Technol., 2023)

Nash double Q-based multi-agent deep reinforcement learning for interactive merging strategy in mixed traffic. - Lin Li 056; Wanzhong Zhao; Chunyan Wang 013; Abbas Fotouhi; Xuze Liu (Expert Syst. Appl., 2024)