Director of Mcity and Bruce D. Greenshields Collegiate Professor of Engineering

Location

2116 GG Brown

2350 Hayward, 2116 GG Brown Ann Arbor, Michigan 48109-2125

Additional TitleS

• Research Professor, University of Michigan Transportation Research Institute
• Director, Center for Connected and Automated Transportation

• Director, Michigan Traffic Lab

Primary Website

Michigan Traffic Lab

Education

• Ph.D. in Civil and Environmental Engineering, University of Wisconsin – Madison, 2000
• B.S. in Automotive Engineering, Tsinghua University, P.R.China, 1993

Research Interests

Prof. Liu conducts interdisciplinary research at the interface between Transportation Engineering, Automotive Engineering, and Artificial Intelligence, with a focus on cyber-physical transportation systems. Specifically, his scholarly interests concern traffic flow monitoring, modeling, and control, testing and evaluation of connected and automated vehicles, and cooperative automated driving.

Prof. Liu’s recent research projects include:

1. Smart Intersections
2. Testing and Evaluation of Automated Vehicles
3. Next Generation Traffic Control Systems

Professional Service

• Managing Editor, Journal of Intelligent Transportation Systems

Publications

Representative Publications:

1. Feng, S., Yan, X., Sun, H., and Liu H. (2021) Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment, Nature Communications, DOI: 10.1038/s41467-021-21007-8
2. Yang, Z., Feng, Y., and Liu, H. (2021) A cooperative driving framework for urban arterials in mixed traffic conditions, Transportation Research Part C: Emerging Technologies, 124, https://doi.org/10.1016/j.trc.2020.102918.
3. Feng S., Feng Y., Yu, C., Zhang Y., and Liu H.X. (2020). Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology. IEEE Transactions on Intelligent Transportation Systems, DOI: 1109/TITS.2020.2972211.
4. Feng S., Feng Y., Sun, H.W., Bao, S., Zhang Y., and Liu H.X. (2020). Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies. IEEE Transactions on Intelligent Transportation Systems, DOI: 1109/TITS.2020.2988309.
5. Wong W., Shen S., Zhao Y. and Liu, H. X. (2019). On the estimation of connected vehicle penetration rate based on single-source connected vehicle data. Transportation Research Part B: Methodological 126, 169-191.
6. Feng, Y., Yu, C., & Liu, H. X. (2018). Spatiotemporal intersection control in a connected and automated vehicle environment. Transportation Research Part C: Emerging Technologies, 89, 364-383.
7. Feng, Y., Zheng, J., & Liu, H. X. (2018). Real-time detector-free adaptive signal control with low penetration of connected vehicles. Transportation Research Record, 2672(18), 35-44.
8. Di, X., Liu, H. X., Pang, J. S., & Ban, X. J. (2013). Boundedly Rational User Equilibria (BRUE): mathematical formulation and solution sets, Transportation Research Part B: Methodological, 57, 300-313.
9. Jabari, S. E., & Liu, H. X. (2013). A stochastic model of traffic flow: Gaussian approximation and estimation. Transportation Research Part B: Methodological, 47, 15-41.
10. Liu, H. X., Wu, X., Ma, W., & Hu, H. (2009). Real-time queue length estimation for congested signalized intersections. Transportation research part C: emerging technologies, 17(4), 412-427.