Journal Papers
- Li, P., Chen, S., Yue, L., Xu, Y. and 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, p.107605.
- Liu, C., Sheng, Z., Li, P., Chen, S., Luo, X. and Ran, B., 2024. “A distributed deep reinforcement learning-based longitudinal control strategy for connected automated vehicles combining attention mechanism”. Transportation Letters, pp.1-17.
- Li, P., Wu, K., Cheng, Y., Parker, S. and 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. and 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, p.104358.
- Li, P., Guo, H., Bao, S. and 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. and Li, P., 2023. “Real-Time Big Data Analytics and Proactive Traffic Safety Management Visualization System”. Journal of Transportation Engineering, Part A: Systems, 149(8), p.04023064.
- Li, P., Abdel-Aty. M, 2022. “A Hybrid Machine Learning Model for Predicting Real-time Secondary Crash Likelihood”. Accident Analysis and Prevention, 165.
- 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.
- 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.
- Li, P., Abdel-Aty, M. and Islam, Z., 2021. “Driving Maneuvers Detection using Semi-Supervised Long Short-Term Memory and Smartphone Sensors”. Transportation Research Record, p.03611981211007483.
- Li, P., Abdel-Aty, M. and Yuan, J., 2020. “Using bus critical driving events as surrogate safety measures for pedestrian and bicycle crashes based on GPS trajectory data”. Accident Analysis & Prevention, 150.
- Li, P., Abdel-Aty. M, Cai, Q. and Islam, Z., 2020. “A Deep Learning Approach to Detect Real-Time Vehicle Maneuvers Based on Smartphone Sensors”. IEEE Transactions on Intelligent Transportation Systems.
- Zhang, S., Abdel-Aty, M., Cai, Q., Li, P. and Ugan, J., 2020. “Prediction of pedestrian-vehicle conflicts at signalized intersections based on long short-term memory neural network”. Accident Analysis & Prevention, 148.
- Li, P., Abdel-Aty, M., Cai, Q. and Yuan, C., 2020. “The application of novel connected vehicles emulated data on real-time crash potential prediction for arterials”. Accident Analysis & Prevention, 144.
- Zhang, S., Abdel-Aty, M., Yuan, J. and and Li, P., 2020. “Prediction of Pedestrian Crossing Intentions at Intersections Based on Long Short-Term Memory Recurrent Neural Network”. Transportation Research Record, p.0361198120912422.
- Li, P., Abdel-Aty, M. and Yuan, J., 2020. “Real-time crash risk prediction on arterials based on LSTM-CNN”. Accident Analysis & Prevention, 135, p.105371.
Conference Papers
Li, P., 2023, Jan. “Exploring Latent Topics from Autonomous Vehicles Crashes and Analyzing Their Relationships with Crash Metadata”. In 102th Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Kusari, A., Li, P., Yang, H., Punshi, N., Rasulis, M., Bogard, S. and 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.
Abdel-Aty, M., Wu, Y., Zheng, O., Li, P., Abdelraouf A., Rim, H., Yuan, J., Gong, Y. and Lee, J., 2022, Jan. “Proactive Traffic Safety Management and Real-time Big Data Visualization System”. In 101st Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty, M., 2022, Jan. “Improving Spatio-temporal Transferability of Real-Time Crash Likelihood Prediction Models Using Transfer Learning Approaches”. In 101st Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty, M., 2022, Jan. “Real-time Secondary Crash Likelihood Prediction Using A Hybrid Machine Learning Model”. In 101st Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty, M., 2021, Jan. “Trajectory Fusion-based Real-Time Crash Likelihood Prediction Using LSTM-CNN with Attention Mechanism”. In 100th Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty, M. and Islam, Z., 2021, Jan. “Driving Behavior Detection Using Semi-supervised LSTM and Smartphone Sensors”. In 100th Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty, M., 2021, Jan. “Using Bus Driving Events as Surrogate Safety Measures for Pedestrian and Bicycle Based on GPS Trajectory Data”. In 100th Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Li, P., Abdel-Aty. M., Cai, Q., and Islam, Z., 2020, Jan. “Real-time Vehicle Maneuvers Detection Based on Smartphone Sensors and Deep Learning”. In 99th Annual Meeting of the Transportation Research Board, Washington D.C., USA.
Zhang, R. and Li, P., 2016, Jan. “Calculation of External costs of Road and Railway Freight Transportation and Internalization”. In 95th Annual Meeting of the Transportation Research Board, Washington D.C., USA.