30 citations · 64 across the 15 of their papers we have counts for
8 papers · 1 filter
Language-Driven Policy Distillation for Cooperative Driving in Multi-Agent Reinforcement Learning
Jiaqi Liu, Chengkai Xu, Peng Hang +4
The cooperative driving technology of Connected and Autonomous Vehicles (CAVs) is crucial for improving the efficiency and safety of transportation systems. Learning-based methods,…
Cooperative Decision-Making for CAVs at Unsignalized Intersections: A MARL Approach with Attention and Hierarchical Game Priors
Jiaqi Liu, Peng Hang, Xiaoxiang Na +2
The development of autonomous vehicles has shown great potential to enhance the efficiency and safety of transportation systems. However, the decision-making issue in complex human…
Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework
Shiyu Fang, Jiaqi Liu, Mingyu Ding +4
At present, Connected Autonomous Vehicles (CAVs) have begun to open road testing around the world, but their safety and efficiency performance in complex scenarios is still not sat…
DDM-Lag : A Diffusion-based Decision-making Model for Autonomous Vehicles with Lagrangian Safety Enhancement
Jiaqi Liu, Peng Hang, Xiaocong Zhao +2
Decision-making stands as a pivotal component in the realm of autonomous vehicles (AVs), playing a crucial role in navigating the intricacies of autonomous driving. Amidst the evol…
Enhancing Social Decision-Making of Autonomous Vehicles: A Mixed-Strategy Game Approach With Interaction Orientation Identification
Jiaqi Liu, Xiao Qi, Peng Hang +1
The integration of Autonomous Vehicles (AVs) into existing human-driven traffic systems poses considerable challenges, especially within environments where human and machine intera…
Brain-Inspired Modelling and Decision-making for Human-Like Autonomous Driving in Mixed Traffic Environment
Peng Hang, Yiran Zhang, Chen Lv
In this paper, a human-like driving framework is designed for autonomous vehicles (AVs), which aims to make AVs better integrate into the transportation ecology of human driving an…
Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Driving
Jingda Wu, Zhiyu Huang, Chao Huang +4
Due to the limited smartness and abilities of machine intelligence, currently autonomous vehicles are still unable to handle all kinds of situations and completely replace drivers.…
Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach
Peng Hang, Chen Lv, Yang Xing +2
Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on roads in the future for a long time, how to merge AVs into human drivers traffic ecology and mi…