Hao Liu

Hao Liu Picture


PATH, Institute of Transportation Studies, University of California, Berkeley
Richmond Field Station, Bldg. 177, Room 11, MC 3580
1357 S. 46th Street, Richmond, CA 94804


Dr. Hao Liu is an Assistant Research Engineer with PATH, where his primary research interest is traffic flow modeling and simulation for traffic streams affected by Connected Automated Vehicles (CAV). He is passionate about extending the traffic flow modeling capability by incorporating latest technology advancements in CAV control, communication, and machine learning. With the modeling tools, he wanted to find out the best traffic operation and management strategies that maximize the benefit of the CAV technologies. He wishes to promote the CAV development, evaluation and deployment by helping researchers over the world implement the PATH simulation models in their tailored CAV studies. His other research interests include arterial traffic management, hardware-in-the-loop simulation, and vehicle energy consumption estimation. Dr. Liu received B.S. in Transportation from Sun Yat-Sen University in China, M.Sc. in Transportation Engineering from Research Institute of Highway in China, and Ph.D. in Civil Engineering from University of Cincinnati.

Recent Publications:

Liu, H., Lu, X. Y., & Shladover, S. E. (2019). Traffic signal control by leveraging Cooperative Adaptive Cruise Control (CACC) vehicle platooning capabilities. Transportation Research Part C: Emerging Technologies104, 390-407.

Kan, X. D., Xiao, L., Liu, H., Wang, M., Schakel, W. J., Lu, X. Y., ... & Ferlis, R. A. (2019). Cross-Comparison and Calibration of Two Microscopic Traffic Simulation Models for Complex Freeway Corridors with Dedicated Lanes. Journal of Advanced Transportation2019.

Zuo, T., Wei, H., Liu, H., & Yang, Y. J. (2019). Bi-level optimization approach for configuring population and employment distributions with minimized vehicle travel demand. Journal of Transport Geography74, 161-172.

Liu, H., Kan, X. D., Shladover, S. E., Lu, X. Y., & Ferlis, R. E. (2018). Modeling impacts of Cooperative Adaptive Cruise Control on mixed traffic flow in multi-lane freeway facilities. Transportation Research Part C: Emerging Technologies95, 261-279.

Liu, H., Kan, X., Shladover, S. E., Lu, X. Y., & Ferlis, R. E. (2018). Impact of cooperative adaptive cruise control on multilane freeway merge capacity. Journal of Intelligent Transportation Systems22(3), 263-275.

Wei, H., Zuo, T., Liu, H., & Yang, Y. J. (2017). Integrating land use and socioeconomic factors into scenario-based travel demand and carbon emission impact study. Urban Rail Transit3(1), 3-14.

Liu, H., Wei, H., Zuo, T., Li, Z., & Yang, Y. J. (2017). Fine-tuning ADAS algorithm parameters for optimizing traffic safety and mobility in connected vehicle environment. Transportation research part C: emerging technologies76, 132-149.

Yao, Z., Wei, H., Li, Z., Ma, T., Liu, H., & Yang, Y. J. (2013). Developing Operating Mode Distribution Inputs for MOVES with a Computer Vision–Based Vehicle Data Collector. Transportation Research Record2340(1), 49-58.

Wei, H., Liu, H., Ai, Q., Li, Z., Xiong, H., & Coifman, B. (2013). Empirical innovation of computational dual‐loop models for identifying vehicle classifications against varied traffic conditions. Computer‐Aided Civil and Infrastructure Engineering28(8), 621-634.