1 citations · 3 across the 5 of their papers we have counts for
5 papers
Hybrid Differential Reward: Combining Temporal Difference and Action Gradients for Efficient Multi-Agent Reinforcement Learning in Cooperative Driving
Ye Han, Lijun Zhang, Dejian Meng +1
In multi-vehicle cooperative driving tasks involving high-frequency continuous control, traditional state-based reward functions suffer from the issue of vanishing reward differenc…
Topology Enhanced MARL for Multi-Agent Cooperative Decision-Making of CAVs
Ye Han, Lijun Zhang, Dejian Meng +1
Decentralized multi-agent cooperative decision-making in continuous environments is fundamentally bottlenecked by the curse of dimensionality, where undirected exploration typicall…
A Value Based Parallel Update MCTS Method for Multi-Agent Cooperative Decision Making of Connected and Automated Vehicles
Ye Han, Lijun Zhang, Dejian Meng +3
To solve the problem of lateral and logitudinal joint decision-making of multi-vehicle cooperative driving for connected and automated vehicles (CAVs), this paper proposes a Monte…
Vehicle Trajectory Prediction based Predictive Collision Risk Assessment for Autonomous Driving in Highway Scenarios
Dejian Meng, Wei Xiao, Lijun Zhang +2
For driving safely and efficiently in highway scenarios, autonomous vehicles (AVs) must be able to predict future behaviors of surrounding object vehicles (OVs), and assess collisi…
RMMDet: Road-Side Multitype and Multigroup Sensor Detection System for Autonomous Driving
Xiuyu Yang, Zhuangyan Zhang, Haikuo Du +7
Autonomous driving has now made great strides thanks to artificial intelligence, and numerous advanced methods have been proposed for vehicle end target detection, including single…