Prof. Meixin ZHU


PhD in Civil Engineering
Affiliate Assistant Professor
Research Area
Research Interests
Autonomous driving
Reinforcement learning
Driving behavior
Traffic signal control

PhD, The University of Washington

Selected Publications

Yang, H., Cai, J., Zhu, M., Liu, C. and Wang, Y., 2022. Traffic-Informed Multi-Camera Sensing (TIMS) System Based on Vehicle Re-Identification. IEEE Transactions on Intelligent Transportation Systems.

Zhu, M., Yang, H.F., Liu, C., Pu, Z. and Wang, Y., 2022. Real-time crash identification using connected electric vehicle operation data. Accident Analysis & Prevention173, p.106708.

Zhu, M., Zhu, W., Lutin, J.M., Cui, Z. and Wang, Y., 2021. Developing a Practical Method to Compute State-Level Bus Occupancy Rate. Journal of Transportation Engineering, Part A: Systems147(6), p.05021001.

Sun, P., Wang, X. and Zhu, M., 2021. Modeling car-following behavior on freeways considering driving style. Journal of transportation engineering, Part A: Systems147(12), p.04021083.

Yang, H., Liu, C., Zhu, M., Ban, X. and Wang, Y., 2021. How fast you will drive? predicting speed of customized paths by deep neural network. IEEE Transactions on Intelligent Transportation Systems23(3), pp.2045-2055.

Wang, H., Zhu, M., Hong, W., Wang, C., Tao, G. and Wang, Y., 2020. Optimizing signal timing control for large urban traffic networks using an adaptive linear quadratic regulator control strategy. IEEE Transactions on Intelligent Transportation Systems23(1), pp.333-343.

Pu, Z., Zhu, M., Li, W., Cui, Z., Guo, X. and Wang, Y., 2020. Monitoring public transit ridership flow by passively sensing Wi-Fi and Bluetooth mobile devices. IEEE Internet of Things Journal8(1), pp.474-486.

Zhu, M., Wang, X. and Hu, J., 2020. Impact on car following behavior of a forward collision warning system with headway monitoring. Transportation research part C: emerging technologies111, pp.226-244.

Zhu, M., Wang, Y., Pu, Z., Hu, J., Wang, X. and Ke, R., 2020. Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving. Transportation Research Part C: Emerging Technologies117, p.102662.

Zhu, M., Wang, X. and Wang, Y., 2018. Human-like autonomous car-following model with deep reinforcement learning. Transportation research part C: emerging technologies97, pp.348-368.

Zhu, M., Wang, X. and Tarko, A., 2018. Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study. Transportation research part C: emerging technologies93, pp.425-445.

Wang, X., Zhu, M., Chen, M. and Tremont, P., 2016. Drivers’ rear end collision avoidance behaviors under different levels of situational urgency. Transportation research part C: emerging technologies71, pp.419-433.

Wang, X., Chen, M., Zhu, M. and Tremont, P., 2016. Development of a kinematic-based forward collision warning algorithm using an advanced driving simulator. IEEE Transactions on Intelligent Transportation Systems17(9), pp.2583-2591.

Honors and Awards

2022 American Statistical Association (ASA) Transportation Statistics Interest Group (TSIG) student paper award

2nd Place, Transportation Forecasting Competition, TRB AI Committee AED50

Most Cited Paper, Transportation Research Part C: Emerging Technologies

Wining Award, 2021 Digital China Innovation Contest

Outstanding Graduates of Shanghai, Shanghai Education Commission, 2017

National Graduate Scholarship (2016, 2017), Ministry of Education, China