Pei Li, Ph.D.

Education

• B.Eng, Logistics Engineering, Tongji University, 2015
• M.Eng, Communication and Transportation Engineering, Tongji University, 2018
• M.S., Smart Cities, University of Central Florida, 2020
• Ph.D., Civil Engineering, University of Central Florida, 2021

 

Research Projects

• (PI) Data Cleansing Automation for Accessible Crash Database Narrative Extracts, $70,000,
  Oct 2024 - Oct 2025, National Highway Traffic Safety Administration.
• (Senior Personnel) Advancing Safety and Emergency Operations through a Regional Connected Vehicle Corridor, $2,000,730, 2025 - 2028, Federal Highway Administration ATTAIN.
• (Co-PI) Traffic Operations Program Management Services, $70,000, Sep 2024 - Sep 2025, Wisconsin Department of Transportation.
• (Co-PI) MAP-21 PM3 and MAPSS Mobility Performance Measures, $120,000, Sep 2024 - Sep
  2025, Federal Highway Administration and Wisconsin Department of Transportation.
• (Senior Personnel) Connected and Automated Vehicle (CAV) Support Program, $200,000,
  July 2024 - Dec 2025, City of Racine.
• (Co-PI) AI in Transportation, $95,000, Aug 2024 - Aug 2025, Wisconsin Department of Transportation.
• (Project Manager) ATMA for Work Zone Safety, $215,715, April 2023 - Sep 2025, U.S. Department of Transportation.
• (Co-PI) Traffic Operations Program Management Services, $70,000, Sep 2023 - Sep 2024, Wisconsin Department of Transportation.
• (Co-PI) MAP-21 PM3 and MAPSS Mobility Performance Measures, $120,000, Sep 2023 - Sep
  2024, Federal Highway Administration and Wisconsin Department of Transportation.

 

Publications

Under Review Articles

• Gan, R., Shi, H., Li, P., Wu, K., An, B., & Ran, B. (2024). Goal-based Neural Physics Vehicle Trajectory Prediction Model. Transportation Research Part C.
• Tamaru, R., Li, P., & Ran, B. (2024). Enhancing Pedestrian Trajectory Prediction with Crowd Trip Information. Expert Systems with Applications.
• Wan, H., Li, P., & Kusari, A. (2024). Demystifying deep reinforcement learning-based autonomous vehicle decision-making. IEEE Transactions on Intelligent Vehicles.
• Wu, K., Li, P., Cheng, Y., Parker, S. T., Ran, B., Noyce, D. A., & Ye, X. (2024). A Digital Twin Framework for Physical-Virtual Integration in V2X-Enabled Connected Vehicle Corridors. IEEE Transactions on Intelligent Vehicles.
• Ma, C., Li, H., Long, K., Zhou, H., Liang, Z., Li, P., Yu, H., Li, X. (2024). Real-Time Identification of Cooperative Perception Necessity in Road Traffic Scenarios. Transportation Research Part C.

 

Journal Articles

• Yin, H., Yue, L., Gong, Y., Li, P., & Huang, Y. (2024). Personalized Lane Departure Warning Based on Non-Stationary Crossformer and Kernel Density Estimation. Alexandria Engineering Journal. 109.
• Li, P., Chen, S., Yue, L., Xu, Y., & Noyce, D. A. (2024). Analyzing relationships between latent topics in autonomous vehicle crash narratives and crash severity using natural language processing techniques and explainable XGBoost. Accident Analysis & Prevention, 203, 107605.
• Liu, C., Sheng, Z., Li, P., Chen, S., Luo, X., & Ran, B. (2024). A distributed deep reinforcement learning-based longitudinal control strategy for connected automated vehicles combining attention mechanism. Transportation Letters, 1-17.
• Li, P., Wu, K., Cheng, Y., Parker, S. T., & Noyce, D. A. (2023). How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials. IEEE Transactions on Intelligent Vehicles.
• Dong, J., Chen, S., Miralinaghi, M., Chen, T., Li, P., & Labi, S. (2023). Why did the AI make that decision? Towards an explainable artificial intelligence (XAI) for autonomous driving systems. Transportation Research Part C: Emerging Technologies, 156, 104358.
• Li, P., Guo, H., Bao, S., & Kusari, A. (2023). A probabilistic framework for estimating the risk of pedestrian-vehicle conflicts at intersections. IEEE Transactions on Intelligent Transportation Systems.
• Abdel-Aty, M., Zheng, O., Wu, Y., Abdelraouf, A., Rim, H., & Li, P. (2023). Real-Time Big Data Analytics and Proactive Traffic Safety Management Visualization System. Journal of Transportation Engineering, Part A: Systems, 149(8), 04023064.
• Li, P., & Abdel-Aty, M. (2022). A hybrid machine learning model for predicting real-time secondary crash likelihood. Accident Analysis & Prevention, 165, 106504.
• Li, P., & Abdel-Aty, M. (2022). Real-time crash likelihood prediction using temporal attention–based deep learning and trajectory fusion. Journal of Transportation Engineering, Part A: Systems, 148(7), 04022043.
• Li, P., Abdel-Aty, M., & Zhang, S. (2022). Improving Spatiotemporal Transferability of Real-Time Crash Likelihood Prediction Models Using Transfer-Learning Approaches. Transportation Research Record: Journal of the Transportation Research Board, 2676(11), 621–631.
• Li, P., Abdel-Aty, M., & Islam, Z. (2021). Driving Maneuvers Detection using Semi-Supervised Long Short-Term Memory and Smartphone Sensors. Transportation Research Record: Journal of the Transportation Research Board, 2675(9), 1386–1397.
• Li, P., Abdel-Aty, M., & Yuan, J. (2021). Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data. Accident Analysis & Prevention, 150, 105924.
• Li, P., Abdel-Aty, M., Cai, Q., & Islam, Z. (2020). A deep learning approach to detect real-time vehicle maneuvers based on smartphone sensors. IEEE Transactions on Intelligent Transportation Systems, 23(4), 3148–3157.
• Li, P., Abdel-Aty, M., Cai, Q., & Yuan, C. (2020). The application of novel connected vehicles emulated data on real-time  crash potential prediction for arterials. Accident Analysis & Prevention, 144.
• Li, P., Abdel-Aty, M., & Yuan, J. (2020). Real-time crash risk prediction on arterials based on LSTM-CNN. Accident Analysis & Prevention, 135, 105371.
• Zhang, S., Abdel-Aty, M., Cai, Q., Li, P., & Ugan, J. (2020). Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network. Accident Analysis & Prevention, 148, 105799.
• Zhang, S., Abdel-Aty, M., Yuan, J., & Li, P. (2020). Prediction of Pedestrian Crossing Intentions at Intersections Based on Long Short-Term Memory Recurrent Neural Network. Transportation Research Record: Journal of the Transportation Research Board, 2674(4), 57–65.

 

Conference Articles

• Gan, R., Shi, H., Li, P., Wu, K., An, B., & Ran, B. (2025). Goal-based Neural Physics Vehicle Trajectory Prediction Model. In Transportation Research Board 104th Annual Meeting.
• Wan, H., Li, P., & Kusari, A. (2025). Demystifying deep reinforcement learning-based autonomous vehicle decision-making. In Transportation Research Board 104th Annual Meeting.
• Zhu, J., Parker, S. T., Li, P., Ran, B., & Noyce, D. A. (2025). A Comprehensive Analysis of Crash Hotspot Identification Methods for Law Enforcement Resource Allocation. In Transportation Research Board 104th Annual Meeting.
• Ma, C., Li, H., Long, K., Liang, Z., Li, P., & Li, X. (2025). Field-Based Identification of Cooperative Perception Necessity in Road Traffic Scenarios. In Transportation Research Board 104th Annual Meeting.
• Wu, K., Gan, R., You, J., Cheng, Y., Li, P., Parker, S. T., & Ran, B. (2025). V2X-LLM: Improving Vehicle-to-Everything Integration and Understanding with Large Language Models. In Transportation Research Board 104th Annual Meeting.
• You, J., Li, P., Cheng, Y., Wu, K., Gan, R., Parker, S. T., & Ran, B. (2024). Real-World Data Inspired Interactive Connected Traffic Scenario Generation. In Transportation Research Board 104th Annual Meeting.
• Li, P., Parker, S. T., & Noyce, D. A. (2024). Automated Vehicles vs. Human Drivers: Modeling Driving Behavior Using Data from Field Experiments. In International Conference on Transportation and Development 2024 (pp. 560-572).
• Wu, K., Li, P., Cheng, Y., Parker, S. T., Ran, B., & Noyce, D. A. (2024). The Enhancement of the Data Pipeline of a  connected Vehicle Corridor: A Leap Towards Digital Twin. In International Conference on Transportation and Development 2024.
• Li, P., Chen, S., Yue, L., Xu, Y., & Noyce, D. A. (2024). Analyzing relationships between latent topics in autonomous vehicle crash narratives and crash severity using natural language processing techniques and explainable XGBoost. In Transportation Research Board 103rd Annual Meeting.
• Li, P., Wu, K., Cheng, Y., Parker, S. T., & Noyce, D. A. (2024). How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials. In Transportation Research Board 103rd Annual Meeting.
• Li, P., Guo, H., Bao, S., & Kusari, A. (2024). A Probabilistic Framework for Estimating the Risk of Pedestrian-vehicle Conflicts at Intersections. In Transportation Research Board 103rd Annual Meeting.
• Yin, H., Yue, L., Li, P., & Sun, J. (2024). Personalized Lane Departure Warning based on Non-Stationary Crossformer and Kernel Density Estimation. In Transportation Research Board 103rd Annual Meeting.
• Wu, K., Cheng, Y., Li, P., Parker, S. T., Ran, B., & Noyce, D. A. (2024). The Enhancement of the Data Pipeline of a Connected Vehicle Corridor: A Leap Towards Digital Twin Implementation. In Transportation Research Board 103rd Annual Meeting.
• Li, P. (2023). Exploring Latent Topics from Autonomous Vehicles Crashes and Analyzing Their Relationships with Crash Metadata. In Transportation Research Board 102th Annual Meeting.
• Kusari, A., Li, P., Yang, H., Punshi, N., Rasulis, M., Bogard, S., & LeBlanc, D. J. (2022, June). Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles. In 2022 IEEE Intelligent Vehicles Symposium (IV) (pp. 829-835). IEEE.
• Li, P., & Abdel-Aty, M. (2022). Real-time Secondary Crash Likelihood Prediction Using A Hybrid Machine Learning Model. In Transportation Research Board 101st Annual Meeting.
• Li, P., & Abdel-Aty, M. (2022). Improving Spatio-temporal Transferability of Real-Time Crash Likelihood Prediction Models Using Transfer Learning Approaches. In Transportation Research Board 101st Annual Meeting.
• Li, P., & Abdel-Aty, M. (2021). Trajectory Fusion-based Real-Time Crash Likelihood Prediction Using LSTM-CNN with Attention Mechanism. In Transportation Research Board 100th Annual Meeting.
• Li, P., & Abdel-Aty, M. (2021). Using Bus Driving Events as Surrogate Safety Measures for Pedestrian and Bicycle Based on GPS Trajectory Data. In Transportation Research Board 100th Annual Meeting.
• Li, P., Abdel-Aty, M., & Islam, Z. (2021). Driving Behavior Detection Using Semi-supervised LSTM and Smartphone Sensors. In Transportation Research Board 100th Annual Meeting.
• Zhang, R., & Li, P. (2016). Calculation of external costs of road and railway freight transportation and internalization. In  Transportation Research Board 95th Annual Meeting (Vol. 16, pp. 2507-2522).