Connected and Autonomous Traffic Research

My research program develops systems of advanced traffic sensing, smart and connected traffic and data mining for traffic safety, mobility, and energy efficiency.

 

 

Selected Projects

  1. PI, Pilot Deployment of Roadside LiDAR in City of Henderson NV, Regional Transportation Commission of Southern Nevada, $86,071, 2018 - 2020

  2. PI, Proof-of-Concept Research of Roadside LiDAR Sensing Multimode Traffic, Nevada Department of Transportation, $313,397, 2018 - 2021

  3. PI, Pilot Applications of Roadside LiDAR Technologies in Washoe County, Regional Transportation Commission – Washoe County, $250,000, 2018 - 2020

  4. 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

  5. PI, Development of a Nevada wildlife-fencing GIS dataset, SOLARIS UTC and Nevada Department of Transportation, $145,817, 2018-2019

  6. PI, University of Nevada Support Services to NDOT Traffic Safety Engineering, Nevada Department of Transportation, $500,000, 2017-2022

  7. PI, Developing a Quality of Signal Timing Performance Measure Methodology for Arterial Operations, Nevada Department of Transportation, $272,986, 2017-2020

  8. PI, High-Resolution Micro Traffic Data from Roadside LiDAR Sensors for Connected-Vehicles and New Traffic Applications, SOLARIS UTC and Nevada Department of Transportation, $173,670, 2017-2018

  9. PI, Safety Benefit-Cost Analysis of Roundabouts, Nevada Department of Transportation, $52,932, 2017

  10. PI, Before-and-after Data Collection of Complete Streets, Nevada Department of Transportation, $40,872, 2017-2018

  11. PI, Correlation Analysis of Nevada Crash Data and ITS Sensor Data, SOLARIS UTC and Nevada Department of Transportation, $52,447, 2016-2017

  12. PI, Horizontal Curve Identification and Estimation, Nevada Department of Transportation, $44,281, 2015-2016

  13. PI, Assessing the Influence of Driver, Vehicle, Roadway and Environment Factors on Pedestrian-Turning-Traffic Crashes at Intersections, SHRP 2, $100,000, 2015

  14. PI, Development of a Comprehensive Crash Database for Nevada that can be used with AASHTOWare Safety Analyst, Nevada Department of Transportation, $210,000, 2014-2017

  15. PI, Interstate 80 and Wildlife Movements within the Pequop and Toano Ranges, Nevada Department of Transportation, $124,117, 2014-2017

  16. PI, SHRP 2 Naturalistic Driving Study Data Usage Guidance for Nevada, SOLARIS UTC, $57,000, 2014-2015

  17. PI, US-50 Wildlife Underpass Evaluation, Nevada Department of Transportation, $77,298, 2014-2015

Selected Papers

  1. Cui, Y., Xu, H., Wu, J. and Wang, A., 2029. Lane Change Identification and Prediction with Roadside LiDAR Data, Optics and Laser Technology, DOI: 10.1016/j.optlastec.2019.105934.

  2. Zhang, Z., Zheng, J., Xu, H., Wang, X., Fan, X. and Chen, R., 2019. Automatic Background Construction and Object Detection Based on Roadside LiDAR. IEEE Transactions on Intelligent Transportation Systems.

  3. Zhao, J., Li, Y., Xu, H. and Liu, H., 2019. Probabilistic Prediction of Pedestrian Crossing Intention Using Roadside LiDAR Data. IEEE Access, 7, pp.93781-93790.

  4. Wu, J., Xu, H., Yue, R., Tian, Z., Tian, Y. and Tian, Y., 2019. An automatic skateboarder detection method with roadside LiDAR data. Journal of Transportation Safety & Security, pp.1-20.

  5. Wu, J. and Xu, 2019. Automatic Vehicle Detection with Roadside LiDAR Data under Rainy and Snowy Conditions, IEEE Intelligent Transportation Systems Magazine, accepted.

  6. Cui, Y., Xu, H., Wu, J., Sun, Y. and Zhao, J., 2019. Automatic Vehicle Tracking with Roadside LiDAR Data for the Connected-Vehicles System. IEEE Intelligent Systems. page(s): 1-8 Print ISSN: 1541-1672, 2019.

  7. Zhang, Y., Yao, E., Zhang, R. and Xu, H., 2019. 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, 76, pp.191-199.

  8. Wu, J., Xu, H., Zheng, Y., Zhang, Y., Lv, B. and Tian, Z., 2019. Automatic Vehicle Classification using Roadside LiDAR Data. Transportation Research Record, p.0361198119843857. Volume: 2673 issue: 6, page(s): 153-164, 2019.

  9. Wu, J., Xu, H., Lv, B., Yue, R. and Li, Y., 2019. Automatic Ground Points Identification Method for Roadside LiDAR Data. Transportation Research Record, p.0361198119843869. Volume: 2673 issue: 6, page(s): 140-152, 2019.

  10. Wu, J., Xu, H. and Liu, W., 2019. Points Registration for Roadside LiDAR Sensors.  Transportation Research Record, p.0361198119843855.

  11. Wu, J. and Xu, H., 2019. Annual Average Daily Traffic Prediction Model for Minor Roads at Intersections. Journal of Transportation Engineering, Part A: Systems, 145(10), p.04019041.

  12. Wu, J., Tian, Y., Xu, H., Yue, R., Wang, A. and Song, X., 2019. Automatic ground points filtering of roadside LiDAR data using a channel-based filtering algorithm. Optics & Laser Technology, 115, pp.374-383.

  13. Yue, R., Yang, G., Tian, Z., Xu, H., Lin, D. and Wang, A., 2019. Microsimulation Analysis of Traffic Operations at Two Diamond Interchange Types. Journal of Advanced Transportation。 2019, Article ID 6863480, 11 pages, 2019.

  14. Zheng, J., Xu, B., Wang, X., Fan, X., Xu, H. and Sun, G., 2019. A portable roadside vehicle detection system based on multi-sensing fusion. International Journal of Sensor Networks, 29(1), pp.38-47.

  15. Zhao, J., Xu, H., Liu, H., Wu, J., Zheng, Y. and Wu, D., 2019. Detection and tracking of pedestrians and vehicles using roadside LiDAR sensors. Transportation research part C: emerging technologies, 100, pp.68-87.

  16. Wu, J., Xu, H., Zheng, Y. and Tian, Z., 2018. A novel method of vehicle-pedestrian near-crash identification with roadside LiDAR data. Accident Analysis & Prevention, 121, pp.238-249.

  17. Wu, J. and Xu, H., 2018. Driver behavior analysis on rural 2-lane, 2-way highways using SHRP 2 NDS data. Traffic injury prevention, 19(8), pp.838-843.

  18. Zhao, J., Xu, H., Wu, J., Zheng, Y. and Liu, H., 2018. Trajectory tracking and prediction of pedestrian's crossing intention using roadside LiDAR. IET Intelligent Transport Systems, 13(5), pp.789-795.

  19. Sun, Y., Xu, H., Wu, J., Zheng, J. and Dietrich, K.M., 2018. 3-D data processing to extract vehicle trajectories from roadside LiDAR data. Transportation research record, 2672(45), pp.14-22.

  20. Wu, J., Xu, H., Sun, Y., Zheng, J. and Yue, R., 2018. Automatic background filtering method for roadside LiDAR data. Transportation Research Record, 2672(45), pp.106-114..

  21. Yang, G., Yue, R., Tian, Z. and Xu, H., 2018. Modeling the Impacts of Traffic Flow Arrival Profiles on Ramp Metering Queues. Transportation Research Record, 2672(15), pp.85-92.

  22. Wu, J., Xu, H. and Zhao, J., 2018. Automatic lane identification using the roadside LiDAR sensors. IEEE Intelligent Transportation Systems Magazine. PP(99):1-1.

  23. Wu, J. and Xu, H., 2018. 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.

  24. Yang, G., Tian, Z., Wang, D. and Xu, H., 2018. Queue length estimation for a metered on-ramp using mesoscopic simulation. Transportation Letters, pp.1-10.

  25. Wu, J. and Xu, H., 2017. Driver behavior analysis for right-turn drivers at signalized intersections using SHRP 2 naturalistic driving study data. Journal of safety research, 63, pp.177-185.

  26. Yang, G., Tian, Z., Xu, H., Wang, Z. and Wang, D., 2018. Impacts of traffic flow arrival pattern on the necessary queue storage space at metered on-ramps. Transportmetrica A: Transport Science, 14(7), pp.543-561.

  27. Sun, Y., Xu, H., Wu, J., Hajj, E.Y. and Geng, X., 2017. Data processing framework for development of driving cycles with data from SHRP 2 Naturalistic Driving Study. Transportation Research Record, 2645(1), pp.50-56.

  28. Wang, Q., Zheng, J., Xu, H., Xu, B. and Chen, R., 2017. Roadside magnetic sensor system for vehicle detection in urban environments. IEEE Transactions on Intelligent Transportation Systems, 19(5), pp.1365-1374.

  29. Yang, G., Wang, Z., Xu, H. and Tian, Z., 2017. Feasibility of using a constant acceleration rate for freeway entrance ramp acceleration lane length design. Journal of Transportation Engineering, Part A: Systems, 144(3), p.06017001.

  30. Yang, G., Tian, Z., Xu, H. and Wang, D., 2016. Queue length estimation at metered freeway‐to‐freeway connectors. Journal of Advanced Transportation, 50(8), pp.1912-1924.

  31. Yang, G., Xu, H., Wang, Z. and Tian, Z., 2016. Truck acceleration behavior study and acceleration lane length recommendations for metered on-ramps. International journal of transportation science and technology, 5(2), pp.93-102.

  32. Geng, X., Liang, H., Xu, H., Yu, B. and Zhu, M., 2016, June. Human-driver speed profile modeling for autonomous vehicle's velocity strategy on curvy paths. In 2016 IEEE Intelligent Vehicles Symposium (IV) (pp. 755-760). IEEE.

  33. Xu, H. and Wei, D., 2016. Improved Identification and Calculation of Horizontal Curves with Geographic Information System Road Layers. Transportation Research Record, 2595(1), pp.50-58.

  34. Yang, G., Tian, Z., Xu, H. and Wang, Z., 2016. Recommendations for acceleration lane length for metered on-ramps. Transportation Research Record, 2588(1), pp.1-11.

  35. Pang, B., Liu, H. and Xu, H., 2016. Calculating Approach Capacity of Diverging Diamond Interchanges with Consideration of Internal Queue Effects. Transportation Research Record, 2553(1), pp.63-71.

  36. Yang, G., Xu, H., Tian, Z. and Wang, Z., 2015. Vehicle speed and acceleration profile study for metered on-ramps in California. Journal of transportation engineering, 142(2), p.04015046.

  37. Wei, D., Xu, H., Kumfer, W., Liu, H. and Wang, Z., 2015. Vehicular traffic capacity at unsignalized crosswalks with probabilistic yielding behavior. Transportation research record, 2483(1), pp.80-90.

  38. Yang, G., Xu, H., Tian, Z., Wang, Z. and Zhao, Y., 2015. Acceleration characteristics at metered on-ramps. Transportation Research Record, 2484(1), pp.1-9.

  39. Xu, H., Liu, H. and Gong, H., 2013. Modeling the asymmetry in traffic flow (a): microscopic approach. Applied Mathematical Modelling, 37(22), pp.9431-9440.

  40. Liu, H., Xu, H. and Gong, H., 2013. Modeling the asymmetry in traffic flow (b): macroscopic approach. Applied Mathematical Modelling, 37(22), pp.9441-9450.

  41. Xu, H., Liu, H., Fernando, H. and Senadheera, S., 2013. Volume-to-Capacity Estimation of Signalized Road Networks for Metropolitan Transportation Planning. Transportation Research Record, 2395(1), pp.93-102.

  42. Xu, H. and Liu, H., 2013. Optimize Evacuation Route Considering the Operational Cost as a Constraint. International Journal of Transportation Science and Technology, 2(1), pp.65-78.

  43. Chen, S., Xu, H. and Liu, H., 2013. Timing oversaturated signals: what can we learn from classic and state-of-the-art signal control models. Journal of Transportation Systems Engineering and Information Technology, 13(1), pp.97-110.

  44. Sun, L., Rong, J., Yao, L., Xu, H. and Liu, H., 2012. Entropy-based estimation of transfers in a terminal. Transportation Planning and Technology, 35(3), pp.303-315.

  45. Xu, H., Liu, H., Tian, Z. and Zhang, W., 2011. Control delay calculation at diverging diamond interchanges. Transportation Research Record, 2257(1), pp.121-130.

 

Selected Publications in Peer-Reviewed Conference Proceedings

  1. Zhao, J., Xu, X. Xia, and H. Liu. 2019. Azimuth-Height Background Filtering Method for Roadside LiDAR Data. IEEE Intelligent Transportation Systems Conference, Auckland, NZ, October 2019.

  2. Tian, Y., Xu, and J. Wu. 2019. A Data Mapping Method for Roadside LiDAR Sensors. IEEE Intelligent Transportation Systems Conference, Auckland, NZ, October 2019.

  3. Wu, J., Xu, H., Zheng, Y., Liu, W., Sun, Y., Yue, R. and Song, X., 2018, November. Driver Behavior Fault Analysis on Ramp-related Crashes/Near-Crashes Using SHRP 2 Naturalistic Driving Study Data. In 2018 21st International Conference on Intelligent Transportation Systems (ITSC) (pp. 2134-2139). IEEE.

  4. Zheng, Y., Xu, H., Tian, Z. and Wu, J., 2018. Design and Implementation of the DSRC-Bluetooth Communication and Mobile Application with LiDAR Sensor.Proceedings of the 97th Transportation Research Board Annual Meeting (No. 18-00691).

  5. Wu, J., Xu, H., Zhao, J. and Simpson, N., 2018. Autonomous Wildlife Crossing Detection Method with Roadside Lidar Sensors.proceedings of the 97th Transportation Research Board Annual Meeting (No. 18-00500).

  6. Xu, H. and Wu, J., 2018. Use of Naturalistic Driving Study data to determine right-turn driver deceleration behavior at signalized intersections.proceedings of the 97th Transportation Research Board Annual Meeting (No. 18-01877).

  7. Zhao, J., Xu, H., Wu, D. and Liu, H., 2018. An artificial neural network to identify pedestrians and vehicles from roadside 360-degree LiDAR data.proceedings of the 97th Transportation Research Board Annual Meeting (No. 18-03129)

  8. Wu, J., Xu, H. and Zheng, J., 2017, October. Automatic background filtering and lane identification with roadside LiDAR data. In 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1-6). IEEE.

  9. Wu, J., Xu, H., Sun, Y. and Geng, X., 2017. Effect of road characteristics and driving cycles on accident risk on full-access-control highways. Proceedings of the 96th Transportation Research Board Annual Meeting (No. 17-00940).