ACADEMICS

Brief Introduction

Dr. Jian Wang earned his doctoral degree in Transportation Engineering from Purdue University in the United States. He is now a faculty member of the School of Transportation at Southeast University. His main research areas include traffic network planning and management, modeling of connected and automated transportation systems, and autonomous driving control. Dr. Wang has led over 10 research projects, including those supported by the National Key R&D Program and the National Natural Science Foundation. He has published over 60 papers in renowned domestic and international journals, including nearly 20 papers in Transportation Research Part A/B/C/E. Dr. Wang has been honored with awards such as the first prize for technical invention from the China Intelligent Transportation Association, the 2020 Best Ph.D. Dissertation Award from the Chinese Overseas Transportation Association (COTA). He has been invited to serve as a reviewer for more than 30 domestic and international journals, including Transportation Research Part A/B/C/E.

Prospective doctoral and master's students with a deep interest in research, and backgrounds in transportation, mathematics, computer science, control, communication, civil engineering, and related fields are welcome to apply.

Selected publication

  1. Wang, J*., He, X., Peeta, S*., Wang, W. (2022). Globally convergent line search algorithm with Euler-based step size-determination method for continuous network design problem. Transportation Research Part B: Methodological, 163, 119-144.

  2. Wang, J., Lu, L.*, Peeta, S. (2022). Real-time deployable and robust cooperative control strategy for a platoon of connected and autonomous vehicles by factoring uncertain vehicle dynamics. Transportation Research Part B: Methodological, 163, 88-118.

  3. Wang, J., Wang, W.*, Ren, G., Yang, M. (2022). Worst-case traffic assignment model for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles by factoring in the uncertain link capacity. Transportation Research Part C: Emerging Technologies, 140, 103703.

  4. Wang, J., Lu, L.*, Peeta, S., He, Z. (2021). Optimal toll design problems for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles. Transportation Research Part C: Emerging Technologies. 125, 102952.

  5. Wang, J., Peeta, S*., Lu, L., Li, T. (2019). Multiclass information flow propagation control under vehicle-to-vehicle communication environments, Transportation Research Part B: Methodological. 129, 96–121.

  6. Wang, J., Gong, S., Peeta, S*., Lu, L. (2019).A real-time deployable model predictive control-based cooperative platooning approach for connected and autonomous vehicles, Transportation Research Part B: Methodological, 128, 271-301.

  7. Wang, J., Peeta, S*., He, S. (2019).Multiclass traffic assignment model for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles, Transportation Research Part B: Methodological, 126, 139–168.

  8. Wang, J., Kim, Y.,He, X., Peeta, S*. (2018). Analytical model for information flow propagation wave under an information relay control strategy in a congested vehicle-to-vehicle communication environment, Transportation Research Part C: Emerging Technologies. 94:1-18.

  9. Wang, J., He, X., Peeta, S*. (2016). Sensitivity analysis based approximation models for day-to-day link flow evolution process. Transportation Research Part B: Methodological, 92, 35-53.

  10. Wang, J.*, Deng, W., Guo, Y. (2014). New Bayesian combination method for short-term traffic flow forecasting. Transportation Research Part C: Emerging Technologies, 43, 79-94.