Zheng (Zane) Li

Zheng_Li.jpg

Connected & Autonomous Transportation Systems Laboratory

6064 McKee Road

Fitchburg, Wisconsin 53719

Hi there 👋! I’m Zane, a Ph.D. student and graduate research assistant in the Department of Civil and Environmental Engineering at the University of Wisconsin–Madison, advised by Prof. Xiaopeng Li. My research focuses on intelligent transportation systems, with particular emphasis on autonomous vehicles, traffic flow theory, and the application of large language models.

Before joining UW–Madison, I earned my master’s degree in transportation engineering from Tongji University, China, under the supervision of Prof. Jian Sun and Prof. Ye Tian.

I aim to understand and model the complex interactions between human drivers, automated driving systems, and traffic control devices. My recent work examines how autonomous vehicle behavior patterns affect traffic dynamics and infrastructure performance, drawing on microscopic simulation, trajectory data analysis, and optimization techniques.

I’m also passionate about bridging transportation engineering and computer science, and I am currently pursuing a Master’s degree in Computer Sciences alongside my Ph.D.

Feel free to explore my work, reach out for collaborations, or connect with me on LinkedIn / Google Scholar. You can also email me at zli2674@wisc.edu.

news

May 31, 2025 My paper Understanding Driver Cognition and Decision-Making Behaviors in High-Risk Scenarios: A Drift Diffusion Perspective has been accepted by Accident Analysis & Prevention. 🧠 This work will be available online soon.
Apr 14, 2025 My paper Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs has been accepted by Communications in Transportation Research. 🚦 This work will be available online soon.
Mar 30, 2025 My paper Leveraging Microscopic Simulation to Enhance the Design of Highway Active Traffic Management Strategies has been accepted by the 2025 36th IEEE Intelligent Vehicles Symposium (IV 2025). 💡 My collaborator will present this work on June 22–25, 2025, in Cluj-Napoca, Romania.
Oct 20, 2024 Several of my recent works have been accepted to TRB 2025 🎉:
  • Assessing Markov Property in Driving Behaviors: Insights from Statistical Tests
  • Understanding Driver Risk Responses and Proactive Decision-Making Behaviors in High-Risk Scenarios
  • Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs
  • Automated Vehicle Longitudinal Stability Analysis: Controller Design and Field Test
I will be attending the conference from Jan 5–9, 2025 in Washington, D.C., to present these works 🚗📊.
Aug 14, 2024 My paper Human Decision-Making in High-Risk Driving Scenarios: A Cognitive Modeling Perspective has been accepted to the 2024 IEEE International Automated Vehicle Validation Conference (IAVVC) 🎉. I will be presenting this work at the conference, which will be held on Oct 21–23, 2024 in Pittsburgh, Pennsylvania 🚗.

selected publications

  1. li2022simulation.png
    Simulation-based optimization of large-scale dedicated bus lanes allocation: Using efficient machine learning models as surrogates
    Zheng Li, Ye Tian, Jian Sun, and 2 more authors
    Transportation Research Part C: Emerging Technologies, 2022
    DOI
    N/A Google Scholar citations
  2. li2025assessing.png
    Assessing Markov Property in Driving Behaviors: Insights from Statistical Tests
    Zheng Li, Haoming Meng, Chengyuan Ma, and 2 more authors
    arXiv preprint arXiv:2501.10625, 2025
    DOI
  3. li2025interaction.png
    Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs
    Zheng Li, Zhipeng Bao, Haoming Meng, and 4 more authors
    Communications in Transportation Research, 2025
    DOI
  4. li2025leveraging.png
    Leveraging Microscopic Simulation to Enhance the Design of Highway Active Traffic Management Strategies
    Zheng Li, Jian Sun, Haoming Meng, and 1 more author
    In 2025 IEEE Intelligent Vehicles Symposium (IV), 2025
    DOI
  5. huang2025understanding.png
    Understanding driver cognition and decision-making behaviors in high-risk scenarios: A drift diffusion perspective
    Heye Huang, Zheng Li, Hao Cheng, and 4 more authors
    Accident Analysis & Prevention, 2025
    DOI