CV

Transportation research
Traffic safety modeling; Traffic operation and prediction; CV data applications.

Methodology
Econometric statistical models; Spatiotemporal ML & DL; Generative AI.

Working topics

• Multi-scale traffic safety modeling with CV data-based driving behaviors
• Network mobility analysis with multi-source traffic data (e.g., CV & ATSPM data)
• Applying generative AI for traffic safety and mobility prediction

2026

Arterial Network Traffic State Prediction with Connected Vehicle Data: An Abnormality-Aware Spatiotemporal Network

MMCAformer: Macro-Micro Cross-Attention Transformer for Traffic Speed Prediction with Microscopic Connected Vehicle Driving Behavior

Real-time Secondary Crash Likelihood Prediction Excluding Post Primary Crash Features

Crash Prediction Under Limited CV Coverage: An Ensemble Deep Learning Model Integrating Multi-Source Traffic Data

Yang, S., Abdel-Aty, M., & Han, L. (2026). Crash prediction under limited CV coverage: an ensemble deep learning model integrating multi-source traffic data. Transportation Research Part C: Emerging Technologies, 183, 105472.

2025

Segment Level Safety Analysis Using Lane-Changing Behavior and Driving Volatility Features from Connected Vehicle Trajectories

Han, L., & Abdel-Aty, M. (2025). Segment level safety analysis using lane-changing behavior and driving volatility features from connected vehicle trajectories. Scientific Reports.

Multiscale Geographical Random Forest: A Novel Spatial ML Approach for Traffic Safety Modeling Integrating Street-View Semantic Visual Features

Cui, P., Abdel-Aty, M., Han, L., & Yang, X. (2025). Multiscale geographical random forest: A novel spatial ML approach for traffic safety modeling integrating street-view semantic visual features. Transportation Research Part C: Emerging Technologies, 179, 105299.

Grouped Random Parameters Poisson-Lindley Model with Spatial Effects Addressing Crashes at Intersections: Insights from Visual Environment Features and Spatiotemporal Instability

Wang, C., Abdel-Aty, M., & Han, L. (2025). Grouped random parameters Poisson-Lindley model with spatial effects addressing crashes at intersections: Insights from visual environment features and spatiotemporal instability. Analytic Methods in Accident Research, 100387.

Intersection Crash Analysis Considering Longitudinal and Lateral Risky Driving Behavior from Connected Vehicle Data: A Spatial Machine Learning Approach

Han, L., & Abdel-Aty, M. (2025). Intersection crash analysis considering longitudinal and lateral risky driving behavior from connected vehicle data: A spatial machine learning approach. Accident Analysis & Prevention, 220, 108180.

Intersection Crash Frequency Analysis Considering Visual Environment Features Using Random Parameter Negative Binomial-Lindley Model

Han, L., Abdel-Aty, M., Joo, Y., Zhai, S., & Wang, D. (2025). Intersection Crash Frequency Analysis Considering Visual Environment Features Using Random Parameter Negative Binomial-Lindley Model. Transportation Research Record, 03611981251353186.

Tunnel Crash Severity and Congestion Duration Joint Evaluation Based on Cross-Stitch Networks

Wang, C., Abdel-Aty, M., & Han, L. (2025). Tunnel crash severity and congestion duration joint evaluation based on cross-stitch networks. Accident Analysis & Prevention, 213, 107942.

Impact of Speed on Injury Severity in Single-Vehicle Run-Off-Road Crashes: Insights from Partially Temporal Constrained Modeling Approach

Wang, Z., Wang, C., Abdel-Aty, M., Han, L., Huang, H., & Tang, J. (2025). Impact of speed on injury severity in single-vehicle run-off-road crashes: Insights from partially temporal constrained modeling approach. Accident Analysis & Prevention, 210, 107848.

2024

Effects of Helmet Usage on Moped Riders’ Injury Severity in Moped-Vehicle Crashes: Insights from Partially Temporal Constrained Random Parameters Bivariate Probit Models

Wang, C., Abdel-Aty, M., Cui, P., & Han, L. (2024). Effects of helmet usage on moped riders injury severity in moped-vehicle crashes: Insights from partially temporal constrained random parameters bivariate probit models. Accident Analysis & Prevention, 208, 107800.

Analyzing Speed-Difference Impact on Freeway Joint Injury Severities of Leading-Following Vehicles Using Statistical and Data-Driven Models

Wang, C., Abdel-Aty, M., Han, L., & Easa, S. M. (2024). Analyzing speed-difference impact on freeway joint injury severities of Leading-Following vehicles using statistical and data-driven models. Accident Analysis & Prevention, 206, 107695.

LSTM + Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data

Han, L., Abdel-Aty, M., Yu, R., & Wang, C. (2024). LSTM + Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data. IEEE Transactions on Intelligent Transportation Systems.

Transformer-Based Modeling of Abnormal Driving Events for Freeway Crash Risk Evaluation

Han, L., Yu, R., Wang, C., & Abdel-Aty, M. (2024). Transformer-based modeling of abnormal driving events for freeway crash risk evaluation. Transportation Research Part C: Emerging Technologies, 165, 104727.

Effects of Speed Difference on Injury Severity of Freeway Rear-End Crashes: Insights from Correlated Joint Random Parameters Bivariate Probit Models and Temporal Instability

Wang, C., Abdel-Aty, M., & Han, L. (2024). Effects of speed difference on injury severity of freeway rear-end crashes: Insights from correlated joint random parameters bivariate probit models and temporal instability. Analytic Methods in Accident Research, 42, 100320.

Utilizing Angle-Based Outlier Detection Method with Sliding Window Mechanism to Identify Real-Time Crash Risk

Gao, Z., Xu, J., Yu, R., & Han, L. (2024). Utilizing angle-based outlier detection method with sliding window mechanism to identify real-time crash risk. Journal of Transportation Safety & Security, 16(2), 157-174.

Improving Model Robustness of Traffic Crash Risk Evaluation via Adversarial Mix-Up Under Traffic Flow Fundamental Diagram

Yu, R., Han, L., Abdel-Aty, M., Wang, L., & Zou, Z. (2024). Improving model robustness of traffic crash risk evaluation via adversarial mix-up under traffic flow fundamental diagram. Accident Analysis & Prevention, 194, 107360.

2023

Driving Risk Assessment Under the Connected Vehicle Environment: A CNN-LSTM Modeling Approach

Zheng, Y., Han, L., Yu, J., & Yu, R. (2023). Driving risk assessment under the connected vehicle environment: a CNN-LSTM modeling approach. Digital Transportation and Safety, 2(3), 211-219.

Effects of Spacing of Highway Roadside Millimeter-Wave Radar Detectors on the Accuracy of a Crash Risk Evaluation Model

YANG Dongfeng, DAI Jie, ZHANG Yueyan, HAN Lei, YU Rongjie. Effects of Spacing of Highway Roadside Millimeter-wave Radar Detectors on the Accuracy of a Crash Risk Evaluation Model[J]. Journal of Transport Information and Safety, 2023, 41(2): 28-35. doi: 10.3963/j.jssn.1674-4861.2023.02.003

2021

Trajectory Data Based Freeway High-Risk Events Prediction and Its Influencing Factors Analyses

Yu, R., Han, L., & Zhang, H. (2021). Trajectory data based freeway high-risk events prediction and its influencing factors analyses. Accident Analysis & Prevention, 154, 106085.

• Programming: Python, R, BUGS (for Bayesian inference modeling), LaTeX
• Software & Tools: VS Code, Cursor, RStudio, WinBUGS, ArcGIS Pro, Zotero, Overleaf, Microsoft Office
• Languages: Chinese (Native), English (Fluent)