About me
Jiawei Wang now is a postdoctoral researcher in Center for Spatial Information Science, The University of Tokyo. Wang received his PhD degree in Civil Engineering (Transportation) from McGill University, supervised by Prof Lijun Sun. During his PhD, he worked on traffic control with machine learning techniques, especially on how to address bus bunching through multi-agent reinforcement learning. He received his B.E. and M.S. degrees from the Department of Intelligent Engineering at Sun Yat-sen University, Guangzhou, China, where he mainly worked on urban network traffic prediction with deep learning.
Research Interests
$\color{#00008b}{\text{Data/AI-Driven}}$ $\color{#00008b}{\text{Traffic}}$ $\color{#00008b}{\text{Analysis:}}$
(Macroscopic) Traffic Flow Prediction
Wang J, Chen R, He Z.
Traffic speed prediction for urban transportation network: A path-based deep learning approach.
Transportation Research Part C: Emerging Technologies, 2019, 100: 372–385.
(Microscopic) Daily Activity Generation
Wang J, Jiang R, Yang C, et al. Large language models as urban residents: An LLM agent framework for personal mobility generation.
NeurIPS, 2024.
(Microscopic) Taxi Behavior Analysis
Cai H, Wang J*, Li B, et al. Understanding the daily operations of electric taxis: From macro-patterns to micro-behaviors.
Transportation Research Part D: Transport and Environment, 2024, 128: 104079.
$\color{#00008b}{\text{Reinforcement}}$ $\color{#00008b}{\text{Learning-based}}$ $\color{#00008b}{\text{Traffic}}$ $\color{#00008b}{\text{Optimization:}}$
Autonomous Vehicle
Wang J, Shi T, Wu Y, et al. Multi-agent graph reinforcement learning for connected automated driving.
ICML Workshop on AI for Autonomous Driving (AIAD), 2020.
Online Taxi Management
Wang J, Cai H, Sun L, et al. MERCI: Multi-agent reinforcement learning for enhancing on-demand electric taxi operations.
Computers & Industrial Engineering, 2024: 110711.
Public Transit Fleet Vehicle
Wang J, Sun L. Dynamic holding control to avoid bus bunching: A multi-agent deep reinforcement learning framework.
Transportation Research Part C: Emerging Technologies, 2020, 116: 102661.
Wang J, Sun L. Reducing bus bunching with asynchronous multi-agent reinforcement learning.
IJCAI 2021.
Wang J, Sun L. Robust dynamic bus control: A distributional multi-agent reinforcement learning approach.
IEEE Transactions on Intelligent Transportation Systems, 2022, 24(4): 4075–4088.
Wang J, Sun L. Multi-objective multi-agent deep reinforcement learning to reduce bus bunching for multi-line services with a shared corridor.
Transportation Research Part C: Emerging Technologies, 2023, 155: 104309.
For complete publication list, please check my Google Scholar
Contact
jiawei-dot-wang4-at-mail-dot-mcgill-dot-ca
Visitors since 2022
