663 citations · 1.3k across the 13 of their papers we have counts for
6 papers · 1 filter
CarPlanner: Consistent Auto-regressive Trajectory Planning for Large-scale Reinforcement Learning in Autonomous Driving
Dongkun Zhang, Jiaming Liang, Ke Guo +5
Trajectory planning is vital for autonomous driving, ensuring safe and efficient navigation in complex environments. While recent learning-based methods, particularly reinforcement…
A Two-stage Based Social Preference Recognition in Multi-Agent Autonomous Driving System
Jintao Xue, Dongkun Zhang, Rong Xiong +2
Multi-Agent Reinforcement Learning (MARL) has become a promising solution for constructing a multi-agent autonomous driving system (MADS) in complex and dense scenarios. But most m…
Zero-shot Transfer Learning of Driving Policy via Socially Adversarial Traffic Flow
Dongkun Zhang, Jintao Xue, Yuxiang Cui +6
Acquiring driving policies that can transfer to unseen environments is challenging when driving in dense traffic flows. The design of traffic flow is essential and previous studies…
Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation
Yuxiang Cui, Longzhong Lin, Xiaolong Huang +3
Safety is of great importance in multi-robot navigation problems. In this paper, we propose a control barrier function (CBF) based optimizer that ensures robot safety with both hig…
Imitation Learning of Hierarchical Driving Model: from Continuous Intention to Continuous Trajectory
Yunkai Wang, Dongkun Zhang, Jingke Wang +3
One of the challenges to reduce the gap between the machine and the human level driving is how to endow the system with the learning capacity to deal with the coupled complexity of…
Learning hierarchical behavior and motion planning for autonomous driving
Jingke Wang, Yue Wang, Dongkun Zhang +2
Learning-based driving solution, a new branch for autonomous driving, is expected to simplify the modeling of driving by learning the underlying mechanisms from data. To improve th…