24 citations · 47 across the 18 of their papers we have counts for
5 papers · 1 filter
Reinforcement Learning from Human Feedback for Lane Changing of Autonomous Vehicles in Mixed Traffic
Yuting Wang, Lu Liu, Maonan Wang +1
The burgeoning field of autonomous driving necessitates the seamless integration of autonomous vehicles (AVs) with human-driven vehicles, calling for more predictable AV behavior a…
iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement
Aoyu Pang, Maonan Wang, Man-On Pun +2
Urban congestion remains a critical challenge, with traffic signal control (TSC) emerging as a potent solution. TSC is often modeled as a Markov Decision Process problem and then s…
Traffic Signal Cycle Control with Centralized Critic and Decentralized Actors under Varying Intervention Frequencies
Maonan Wang, Yirong Chen, Yuheng Kan +4
Traffic congestion in urban areas is a significant problem, leading to prolonged travel times, reduced efficiency, and increased environmental concerns. Effective traffic signal co…
A Multi-Agent Rollout Approach for Highway Bottleneck Decongestion in Mixed Autonomy
Lu Liu, Maonan Wang, Man-On Pun +1
The integration of autonomous vehicles (AVs) into the existing transportation infrastructure offers a promising solution to alleviate congestion and enhance mobility. This research…
LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments
Maonan Wang, Aoyu Pang, Yuheng Kan +3
Traffic congestion in metropolitan areas presents a formidable challenge with far-reaching economic, environmental, and societal ramifications. Therefore, effective congestion mana…