1 code implementation • 13 Mar 2024 • Maonan Wang, Aoyu Pang, Yuheng Kan, Man-on Pun, Chung Shue Chen, Bo Huang
Specifically, a hybrid framework that augments LLMs with a suite of perception and decision-making tools is proposed, facilitating the interrogation of both the static and dynamic traffic information.
1 code implementation • 8 Dec 2023 • Maonan Wang, Xi Xiong, Yuheng Kan, Chengcheng Xu, Man-on Pun
Traffic congestion is a persistent problem in urban areas, which calls for the development of effective traffic signal control (TSC) systems.
no code implementations • 8 Aug 2023 • Xi Xiong, Maonan Wang, Dengfeng Sun, Li Jin
To simplify the problem, we decouple the action space by prioritizing routing decisions based on travel time estimation.
no code implementations • 24 Oct 2022 • Maonan Wang, Yutong Xu, Xi Xiong, Yuheng Kan, Chengcheng Xu, Man-on Pun
In this paper, we propose a novel reinforcement learning approach with augmented data (ADLight) to train a universal model for intersections with different structures.