Our team's research in the field of intelligent driving assistance specifically includes security state estimation and analysis, and security risk control. The estimation, analysis and control of traffic safety risks are important links to ensure the personal safety of traffic participants. With the development of advanced technologies such as the Internet of Vehicles, intelligent networked vehicles, and vehicle-road coordination systems, the diversification of data sources has brought more opportunities for traffic safety status estimation, traffic safety status analysis, and traffic safety risk management and control. Real-time, accurate and effective management and control of security risks. Safety state estimation and analysis include accident risk prediction of expressways, ramps, and expressway interweaving sections, safety analysis of time and space factors, and safety assessment in an autonomous driving environment. Safety risk control includes the implementation of control over expressways, ramps, and interweaving sections to improve highway safety. The following figure shows the scenarios covered by the team in the field of security risk management and control, and shows the latest research.
Wang, L., Zhong, H., Huang, W., & Ma, W.* (2020). Pedestrian Spatial Violation Analyses for Urban Roadways. ASCE‘s Journal of Transportation Engineering, Part A: Systems.146(11):04020125.
Wang, L., Zhong, H., Ma, W., Abdel-Aty, M., & Park, J. (2020). How Many Crashes Can Connected and Automated Vehicle Technologies Prevent: a Meta-analysis. Accident Analysis & Prevention, 105299.
Wang, L., Zhong, H., Ma, W., & Zhong, Y. (2020). Multi-source Data-Driven Prediction for Dynamic Pick-up Demand of One-way Carsharing Systems. Transportmetrica B: Transport Dynamics, 8(1): 90-107.
Wu, Z., Zeng, X., & Wang, L. * (2020). A New Traffic Conflict Measure for Electric Bicycles at Intersections. Journal Promet - Traffic & Transportation, 32(3): 309-320.
Wang, L., Abdel-Aty, M., Lee, J., & Shi, Q. (2019). Analysis of Real-time Crash Risk for Expressway Ramps Using Traffic, Geometric, Trip Generation, and Socio-Demographic Predictors. Accident Analysis & Prevention, 122, 378-384. (ESI Top 1%)
Wang, L., Abdel-Aty, M., Ma, W., Hu, J., & Zhong, H. (2019). Quasi-vehicle-trajectory-based real-time safety analysis for expressways. Transportation Research Part C: Emerging Technologies, 103, 30-38.
Wang, L., Liu, Q., & Ma, W. (2019). Optimization of dynamic relocation operations for one-way electric carsharing systems. Transportation Research Part C: Emerging Technologies, 101, 55-69.
Wang, L., Jin, Y., Wang, L.*, Ma, W., & Li, T. (2019). Incentive-Based Approach to Control Demands for Operation of One-Way Carsharing System. Transportation Research Record: Journal of the Transportation Research Board, 2673, 427-438. (Corresponding author).
Wang, L., Abdel-Aty, M., Wang, X., & Yu, R. (2018). Analysis and Comparison of Safety Models Using Average Daily, Average Hourly, and Microscopic Traffic. Accident Analysis & Prevention, 111, 271-279.
Huang, S., Yang, X., Wang, L. *, Chen, W., Zhang, F., & Dong, D. (2018). Two-stage turnout fault diagnosis based on similarity function and fuzzy c-means. Advances in Mechanical Engineering, 10(12), 1687814018811402.
Wang, L., Abdel-Aty, M., & Lee, J. (2017). Implementation of Active Traffic Management Strategies for Safety of a Congested Expressway Weaving Segment. Transportation Research Record: Journal of the Transportation Research Board, 2635, 28-35.
Wang, L., Abdel-Aty, M., & Lee, J. (2017). Safety Analytics for Integrating Crash Frequency and Real-Time Risk Modeling for Expressways. Accident Analysis & Prevention, 104, 58-64.
Wang, J., Abdel-Aty, M., & Wang, L.* (2017). Examination of the Reliability of the Crash Modification Factors using Empirical Bayes Method with Resampling Technique. Accident Analysis & Prevention, 104, 96-105. (Corresponding author).
Wang, L., & Abdel-Aty, M. (2016). Microscopic Safety Evaluation and Prediction for Freeway-to-Freeway Interchange Ramps. Transportation Research Record: Journal of the Transportation Research Board, 2583, 56-64.
Wang, L., Shi, Q., & Abdel-Aty, M. (2015). Predicting Crashes on Expressway Ramps with Real-Time Traffic and Weather Data. Transportation Research Record: Journal of the Transportation Research Board, 2514, 32-38.
Wang, L., Abdel-Aty, M., Shi, Q., & Park, J. (2015). Real-time crash prediction for expressway weaving segments. Transportation Research Part C: Emerging Technologies, 61, 1-10.
Latest Publications：
Ziliang He, Wanjing Ma, Ling Wang, Hao Zhong, Chunhui Yu. Vehicle Group Crash Risk Prediction based Active Traffic Management Strategies for Expressways. 100th Annual Meeting of the Transportation Research Board. Accepted.
Kang Wang, Ling Wang, Wanjing Ma, Hao Zhong, Hongge Zhu. Real-time Crash Prediction for Expressways Considering Segment Type Heterogeneity. 100th Annual Meeting of the Transportation Research Board. Accepted.
Accepted:
1. Ling Wang, Hao Zhong, Ziliang He, Wanjing Ma, Chunhui Yu. A vehicle head-up display system for safety assistance functions, 202010074312.2.
2. Ling Wang, Hao Zhong, Wanjing Ma, Chunhui Yu. A calculation method for the reduction of accidents of intelligent connected vehicles, 201911332356.4.
3.Ma Wanjing, he Ziliang, Wang Ling, Yu Chunhui. A coordinated control method of Expressway speed and ramp based on accident risk. 202010935327.3
4. Wang Ling, Zhong Hao, Ma Wanjing, Yu Chunhui. A real-time accident risk prediction of Expressway Based on quasi vehicle trajectory. 202010846934.2
5. Wang Ling, Wang Kang, Ma Wanjing, Yu Chunhui. A real-time prediction method of Expressway accident risk based on road segment heterogeneity. 202011106542.9
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