Qingyi Liang — accepted AI-conference papers

2024

Attention-Based Distributional Reinforcement Learning for Safe and Efficient Autonomous Driving

Jia Liu, Jianwen Yin, Zhengmin Jiang, Qingyi Liang, Huiyun Li

RA-L 2024

Autonomous driving vehicles play a critical role in intelligent transportation systems and have garnered considerable attention. Currently, the popular approach in autonomous driving systems is to design separate optimal objectives for each independent module. Therefore, a major concern arises from

Cited by 9 Source ↗Scholar ↗

2024

Limited Information Aggregation for Collaborative Driving in Multi-Agent Autonomous Vehicles

Qingyi Liang, Jia Liu, Zhengmin Jiang, Jianwen Yin, Kun Xu, Huiyun Li

RA-L 2024

Multi-agent reinforcement learning (MARL) methods have emerged as a promising solution for multi-agent collaborative driving in the intersection and roundabout scenarios. However, these methods need large amounts of training data obtained from the interaction with the driving simulator, and learning

Cited by 13 Source ↗Scholar ↗