Dr. Hao Liu is a Post-Doctoral researcher at PATH in Dr. Steven Shladover’s team, where he works on traffic flow modeling and simulation for traffic stream affected by the Corporative Adaptive Cruise Control (CACC) systems. He received his B.S. in Transportation Engineering from Sun Yat-Sen University in China, M.Sc. in Transportation from Research Institute of Highway in China, and Ph.D. in Civil Engineering from University of Cincinnati. His dissertation research focuses on evaluating the effectiveness of Connected Vehicle (CV) technology on the traffic performance regarding mobility, safety and environment. In addition to the CV effectiveness modeling, he has 9 years of experience in microscopic traffic flow modeling, driving behavior modeling, on-road air quality modeling, traffic safety analysis, and traffic simulation software development. He was the major researcher in a U.S. Environmental Protection Agency (EPA) supported project that aims to identify the interactions among the land-use adaptation, the travel demand patterns and the traffic flow operations. The quantified understanding of such interactions are essential to determine the land-use development plans and travel demand management strategies that enable the optimal environment performance of a region. He also participated in a project supported by the Federal Highway Administration (FHWA) and Ohio Department of Transportation (ODOT). In this project, he was in charge of developing a framework for predicting the on-road PM2.5 emissions based on traffic data available from various sources.
Liu, H., Wei, H., Zuo, T., Li, Z., and Yang, J. (2017). “Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic Safety and Mobility in Connected Vehicle Environment”. Submitted to Transportation Research Part C: Emerging Technologies, Volume 76, Pages 132-149.
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 Engineering, 28(8), 621-634.
Liu, H., Wei, H., Yao, Z., Ren, H., & Ai, Q. (2013). Modeling and Evaluating Short-Term On-Road PM2.5 Emission Factor Using Different Traffic Data Sources. Proceedings of 93rd Annual Meeting of the Transportation Research Board, Washington D.C.
Liu, H., Wei, H., Yao, Z., Ai, Q., & Ren, H. (2013). Effects of Collision Avoidance System on Driving Patterns in Curve Road Conflicts. Procedia- Social and Behavioral Sciences, 96, 2945-2952.
Liu, H., Wei, H., & Yao, Z. (2012). Modeling ITS data sources for generating realistic traffic operating parameters for project-level conformity analysis. In Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on (pp. 1912-1917). IEEE.
Liu, H., Wei, H., Yao, Z., Ai, Q., & Li, B. (2012). Empirical Identification and Quantification of Driver Anticipation Factor in Car-Following Behavior Modeling. Proceedings of 92nd Annual Meeting of the Transportation Research Board, Washington D.C.
Liu, H., Wei, H., Ai, Q., Li, Z., Coifman, B., & Wang, H. (2012). Clarifying Traffic Flow Phase for Vehicle Classifications using Dual-loop Data. Proceedings of 12nd COTA International Conference of Transportation Professionals.
Liu, H., Wei, H., Yao, Z., & Ai, Q. (2012). Estimating Emission Impact of Traffic Flow Operation with Dual-loop Data. Proceedings of 12nd COTA International Conference of Transportation Professionals.