Xiaowei (Tom) Shi

Dr. Shi’s research focuses on evaluating existing emerging mobility technologies, such as automated, connected, and electric vehicles, and developing novel technologies through the utilization of field experiments and hardware-in-the-loop methodologies. His research integrates transportation engineering, control engineering, optimization, and data science. His works have been published in top transportation journals, e.g., Transportation Science, Transportation Research Parts B & C.

View Dr. Shi's website.

Education

• • PhD, Transportation, Civil and Environmental Engineering, 2021, University of South Florida
  • MS, Transportation, Civil and Environmental Engineering, 2020, University of South Florida
  • MS, Control Science and Engineering, Traffic and Transportation, 2018, Beijing Jiaotong University
  • BE, Urban Rail Transit, Traffic and Transportation, 2015, Beijing Jiaotong University

Research interests

• • Evaluation and Testing of Connected and Automated Vehicles (CAVs)
  • Development of Vehicle Automation and Vehicle-to-everything (V2X) Communications Technologies
  • Hardware-in-the-loop Testing for Cooperative Driving Automation (CDA) Systems

Selected Publications

Google Scholar Link

• • Shi, X. and Li, X.*, 2023. Trajectory Planning for an Autonomous Vehicle with Conflicting Moving Objects over a Fixed Path. Transportation Research Part B: Methodological. https://doi.org/10.1016/j.trb.2023.05.001
  • Shi, X., Yao, H., Liang, Z. and Li, X.*, 2022. An Empirical Study on Fuel Consumption of Commercial Automated Vehicles. Transportation Research Part D: Transport and Environment. https://doi.org/10.1016/j.trd.2022.103253
  • Shi, X. and Li, X.*, 2021. Operations Design of Modular Vehicles on an Oversaturated Corridor with First-in-first-out Passenger Queueing. Transportation Science. https://doi.org/10.1287/trsc.2021.1074
  • Shi, X. and Li, X.*, 2021. Constructing Fundamental Diagram for Traffic Flow with Automated Vehicles: Methodology and Demonstration. Transportation Research Part B: Methodological. https://doi.org/10.1016/j.trb.2021.06.011
  • Shi, X. and Li, X.*, 2021. Empirical Study on Car Following Characteristics of Automated Vehicles with Different Headway Settings. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2021.103134
  • Shi, X., Zhao, D., Yao, H. and Li, X.*, 2021. Video-based Trajectory Generation for High-Granularity Highway Simulation (HIGH-Sim). Communications in Transportation Research. https://doi.org/10.1016/j.commtr.2021.100014
  • Wang, Z., Shi, X.*, Zhao, X. and Li, X., 2021. Modeling Decentralized Mandatory Lane Change for Connected and Autonomous Vehicles. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2021.103441
  • Shi, X., Wang, Z., Li, X.* and Pei, M., 2021. The Effect of Ride Experience on Changing Opinions Toward Autonomous Vehicle Safety. Communications in Transportation Research. https://doi.org/10.1016/j.commtr.2021.100003
  • Shi, X., Chen, Z., Pei, M. and Li, X.*, 2020. Variable-Capacity Operations with Modular Transits for Shared-Use Corridors. Transportation Research Record. https://doi.org/10.1177/0361198120928077
  • Shi, X.*, Liu, H., Wang, M., Li, X., Ciuffo, B., Work, D., and Kan, D., 2023. Inconsistency of AV Impacts on Traffic Flow: Predictions in Literature. Road Vehicle Automation 10. https://doi.org/10.1007/978-3-031-34757-3_13
  • Wang, Z., Shi, X. and Li, X.*, 2019. Review of lane-changing maneuvers of connected and automated vehicles: models, algorithms, and traffic impact analyses. Journal of the Indian Institute of Science. https://link.springer.com/article/10.1007/s41745-019-00127-7

Community Involvement

• • IEEE Emerging Transportation Technology Testing (ET3) Technical Committee
  • Transportation Research Board (TRB)-AEP40 (5) Emerging Technologies in Network Modeling