📝 Publications

[1] V2X-Lead: Lidar-based End-to-End Autonomous Driving with Vehicle-to-Everything Communication Integration. Zhiyun Deng, Yanjun Shi, and Weiming Shen.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023.

• Utilized vehicle-to-everything communication to enhance the safety and efficiency of an end-to-end autonomous driving agent trained by a reinforcement learning algorithm, particularly when the agent’s vision is obstructed by other vehicles in mixed-autonomy traffic.

[2] Cooperative Platoon Formation of Connected and Autonomous Vehicles: Towards Efficient Merging Coordination at Unsignalized Intersections. Zhiyun Deng, Kaidi Yang, Weiming Shen, and Yanjun Shi.

IEEE Transactions on Intelligent Transportation Systems (IEEE TITS), 2023.

• Proposed a bi-level optimization method that can jointly optimize the passing sequences and trajectories of vehicles at traffic intersections, effectively enhancing the safety of vehicle interaction and improving overall traffic efficiency.

[3] A Coevolutionary Algorithm for Cooperative Platoon Formation of Connected and Automated Vehicles. Zhiyun Deng, Jiaxin Fan, Yanjun Shi, and Weiming Shen.

IEEE Transactions on Vehicular Technology (IEEE TVT), 2022.

• Developed a trajectory planning method that reduced fuel consumption for platoons of vehicles (where vehicles travel closely together in a group, like a virtual train) on highways, enabling more eco-friendly and cost-effective transportation.

[4] A Conflict Duration Graph-based Coordination Method for Connected and Automated Vehicles at Signal-Free Intersections. Zhiyun Deng, Yanjun Shi, Qiaomei Han, Lingling Lv, and Weiming Shen.

Applied Sciences, 2020.

• Developed a trajectory planning method that prioritized passenger comfort by minimizing the number of sudden stops and starts at traffic intersections, resulting in a more pleasant and enjoyable travel experience.