Hao Xu
- Phone: (775) 784-6909
- Email: haox@unr.edu
- Building: SEM
- Room: 223
- Mailstop: 0258
- Website: Dr. Xu's website
Dr. Hao Xu is an associate professor in the Department of Civil and Environmental Engineering at the University of Nevada, Reno. His research areas include collection and analysis of roadside LiDAR data, vehicle operation cost evaluation, driving behavior analysis with naturalistic driving study data, intelligent transportation systems including connected vehicles, and data-driven traffic safety analysis.
Dr. Xu has managed approximately $3,000,000 research projects as PI or Co-PI, and has published extensively with findings from the research. Dr. Xu is the registered professional engineer in Nevada. He is the invited member of the Traffic World Conference on Transport Research Society (WCTRS).
Dr. Xu keeps close collaboration relationship with local transportation agencies such as the City of Reno, the Washoe County Regional Transportation Commission (RTC), the Nevada Department of Transportation (NDOT).
Dr. Xu has been working with multidisciplinary researchers on autonomous/connected vehicles, cybersecurity of transportation systems and smart cities. In the past one and half year, Dr. Xu has been leading the unique and innovative research on the technologies of roadside LiDAR deployment at the University of Nevada, Reno and has developed a series of methodologies to extract high-accuracy LiDAR trajectory data of all road users, which could be a promising solution of the CAV data gap and is expected to bring revolutionary changes to future traffic systems. The collaboration between Dr. Xu’s research team, RTC Washoe County, and the City of Reno has implemented the world-first LiDAR-enhanced connected intersection in Reno Nevada. Dr. Xu has been leading development of the vehicle-infrastructure connected-vehicle testing environment at the University of Nevada, Reno.
- Ph.D., Transportation Engineering, Texas Tech University, 2011
- M.S., Transportation Engineering, Texas Tech University, 2009
- M.E., Automation, University of Science and Technology of China, 2007
- B.E., Automation, University of Science and Technology of China, 2004
Prospective graduate students
Dr. Xu has research assistant scholarships for new Ph.D. students. The positions will be involved in the following research topics:
- Big data analysis of traffic crashes and intelligent transportation real-time sensor data
- Automatic traffic data survey system with videos and 360-degree LIDAR sensors
- Data analysis of latest driver behavior and vehicle sensor data from U.S. Federal Highway Administration
- Traffic crash prediction modeling
Research interests
- Collection and analysis of roadside LiDAR data
- Vehicle operation cost evaluation
- Driving behavior analysis with naturalistic driving study data
- Intelligent transportation systems including connected vehicles
- Data-driven traffic safety analysis
Grants received
- PI, Pilot Deployment of Roadside LiDAR in City of Henderson NV, Regional Transportation Commission of Southern Nevada, $86,071, 2018 - 2019
- PI, Proof-of-Concept Research of Roadside LiDAR Sensing Multimode Traffic, Nevada Department of Transportation, $313,397, 2018 - 2021
- PI, Pilot Applications of Roadside LiDAR Technologies in Washoe County, Regional Transportation Commission – Washoe County, $250,000, 2018 - 2020
- PI, Data Collection of Wildlife Animals Crossing I80 in Eastern Nevada and USA Parkway, SOLARIS UTC and Nevada Department of Transportation, $136,051, 2018-2019
- PI, Development of a Nevada wildlife-fencing GIS dataset, SOLARIS UTC and Nevada Department of Transportation, $145,817, 2018-2019
- PI, University of Nevada Support Services to NDOT Traffic Safety Engineering, Nevada Department of Transportation, $500,000, 2017-2022
Selected publications
- Yao, E., H. Xu, R. Zhang, Y. Zhang “Analysis of Elderly People’s Travel Behaviors during the Morning Peak Hours in the Context of the Free Bus Program in Beijing, China”, Journal of Transport Geography, in press, 2019.
- Wu, J., H. Xu, Y. Zheng, Y. Zhang, B. Lv and Z. Tian, “Automatic Vehicle Classification using Roadside LiDAR Data”, Transportation Research Record: Journal of the Transportation Research Board, 2019 accepted.
- Wu, J., H. Xu, B. Lv, R. Yue and Y. Li, “Automatic Ground Points Identification Method for Roadside LiDAR Data”, Transportation Research Record: Journal of the Transportation Research Board, 2019 accepted.
- Wu, J., H. Xu, and W. Liu, “Points Registration for Roadside LiDAR Sensors”, Transportation Research Record: Journal of the Transportation Research Board, 2019 accepted.
- Wu, J., H. Xu, and C. Reider, “Annual Average Daily Traffic Prediction Model for Minor Roads at Intersections”, ASCE’s Journal of Transportation Engineering, Part A: Systems, Accepted, 2019.
- Song, X., Y. Tian, H. Xu, J. Wu, R. Yue, and A. Wang, “Automatic Ground Points Filtering of Roadside LiDAR Data Using a Channel-Based Filtering Algorithm”, Optics and Laser Technology Volume 115, Pages 374-383, 2019.
- Yue, R., G. Yang, Z. Tian, H. Xu, D. Lin and A. Wang, “Microsimulation Analysis Of Traffic Operations At Two Diamond Interchange Types”, Journal of Advanced Transportation, vol. 2019, Article ID 6863480, 11 pages, 2019.
- Zheng, J., B. Xu, X. Wang, X. Fan, H. Xu and G. Sun, “A portable roadside vehicle detection system based on multi-sensing fusion”, International Journal of Sensor Networks, Vol. 29, N. 1, 2019, Pages 38-47.
- Zhao, J., H. Xu, H. Liu and J. Wu, “Detection and Tracking of Pedestrians and Vehicles using Roadside LiDAR Sensors”, Transportation Research Part C, Volume 100, Pages 68-87, 2019.
- Wu, J., H. Xu, Y. Zheng and Z. Tian, “A Novel Method of Vehicle-Pedestrian Near-Crash Identification with Roadside LiDAR Data”, Accident Analysis & Prevention, Volume 121, December 2018, Pages 238-249.
- Wu, J. and H. Xu, “Driver Behavior Analysis on Rural Two-lane, Two-way Highways using SHRP 2 NDS Data”, Traffic Injury Prevention, Volume 19, 2018 - Issue 8, Pages 838-843.
- Zhao, J., H. Xu, J. Wu, Y. Zheng and H. Liu, “Tracking and Prediction of Pedestrian Behavior at Intersection Crossings using Roadside LiDAR”, IET Intelligent Transport Systems, 10.1049/iet-its.2018.5258., 2018.
- Sun, Y., H. Xu, J. Wu, J. Zheng and K. Dietrich, “3-D Data Processing to Extract Vehicle Trajectories from Roadside LiDAR Data”, Transportation Research Record: Journal of the Transportation Research Board, 0361198118775839, 2018.
- Wu, J., H. Xu, Y. Sun, J. Zheng and R. Yue, “Automatic Background Filtering Method for Roadside LiDAR Data”, Transportation Research Record: Journal of the Transportation Research Board, 0361198118775841, 2018.
- Yang, G., R. Yue, Z. Tian and H. Xu, “Modeling the Impacts of Traffic Flow Arrival Profiles on Ramp Metering Queues”, Transportation Research Record: Journal of the Transportation Research Board, 0361198118782253, 2018.
- Wu, J., H. Xu, J. Zhao. “Automatic Lane Identification using the Roadside LiDAR Sensors”, IEEE Intelligent Transportation Systems Magazine, PP(99):1-1 · October 2018.
- Wu, J. and H. Xu. “The Influence of Road Familiarity on Distracted Driving Activities and Driving Operation using Naturalistic Driving Study Data”, Transportation Research Part F: traffic psychology and behavior, 52, pp.75-85, 2018.
- Yang, G., Z Tian, D Wang and H Xu, “Queue length estimation for a metered on-ramp using mesoscopic simulation”, Transportation Letters, 1-10, 2018.