主要研究方向
自动驾驶行为建模与控制优化、端到端算法测试与场景生成、智能驾驶人机交互、智能网联交通系统等
近期项目
近期主持项目：
·国家自然科学基金优秀青年科学基金项目（overseas）-智能网联混合交通流建模与控制优化- 2025-2028，主持
·国家自然科学基金面上项目-面向交通智能体训练优化的交通物理世界模型构建方法- 2027-2030，主持
·国家自然科学基金青年科学基金项目（C类）-自动驾驶汽车交互解析及效能影响评估- 2026-2028，主持
·上海市晨光计划项目- 2026-2027，主持
·同济大学青年百人A岗高层次人才科研项目-自动驾驶汽车评估测试及决策优化- 2026-2029，主持
·重庆理工大学合作项目- 2025-2026，主持
·重庆机电大学合作项目- 2026-2027，主持
近期参与项目：
·国家重点研发计划“交通载运装备与智能交通技术”重点专项自主式交通系统计算技术，2023-2026
·深智城集团交通垂域大模型项目，2026-2027
·教育部自动驾驶交通学科突破先导项目，2025-2029
·基金委卓越研究群体项目“自动驾驶交通智能控制”，2025-2029
获奖情况
2026，《中国公路学报》优秀审稿专家
2025,上海市晨光学者
2023，上海市白玉兰人才计划（海外）
2023，第一届Onsite自动驾驶算法挑战赛-高速路赛第三名（作为指导教师带队）
2023，威斯康辛研究资助竞赛奖
2022，威斯康辛智能交通协会奖
2021，IEEE“塑造智能交通未来”一等奖
2017，天津大学优秀毕业生
发表刊物
最新发表情况见Google Scholar:
https://scholar.google.com/citations?user=_YbzjdUAAAAJ&hl=en
部分代表性论著（*表示通讯作者）：
1.Shi, H., Chen, D., Zheng, N., Wang, X., Zhou, Y*., & Ran, B. (2023). A deep reinforcement learning based distributed control strategy for connected automated vehicles in mixed traffic platoon.Transportation Research Part C: Emerging Technologies, 148, 104019. (SCI, JIF: 7.6, Q1)
2.Shi, H., Zhou, Y*., Wang, X., Fu, S., Gong, S., & Ran, B. (2022). A deep reinforcement learning-based distributed connected automated vehicle control under communication failure.Computer-Aided Civil and Infrastructure Engineering, 37(15), 2033–2051. (SCI, JIF: 8.5, Q1)
3.Shi, H., Zhou, Y*., Wu, K., Wang, X., Lin, Y., & Ran, B. (2021). Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment.Transportation Research Part C: Emerging Technologies, 133, 103421. (SCI, JIF: 7.6, Q1)
4.Shi, H., Nie, Q., Fu, S., Wang, X., Zhou, Y*., & Ran, B. (2021). A distributed deep reinforcement learning–based integrated dynamic bus control system in a connected environment.Computer-Aided Civil and Infrastructure Engineering, 36(9), 1147–1164. (SCI, JIF: 8.5, Q1)
5.Shi, H., Zhou, Y., Wu, K., Chen, S., Ran, B., & Nie, Q. (2023). Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles.Knowledge-Based Systems, 110485. (SCI, JIF: 7.2, Q1)
6.Shi, H., Dong, S., Wu, Y., Nie, Q., Zhou, Y., & Ran, B. (2024). Generative adversarial network for car following trajectory generation and anomaly detection.Journal of Intelligent Transportation Systems, 28(1), 1–14. (SCI, JIF: 2.8, Q2)
7.Wu, K., Zhou, Y.,Shi, H*., Li, X., & Ran, B. (2023). Graph-Based Interaction-Aware Multimodal Vehicle Trajectory Prediction.IEEE Transactions on Intelligent Vehicles, 9(2), 3630–3643. (SCI, JIF: 14.0, Q1)
8.Nie, Q., Ou, J., Zhang, H., Li, S., Lu, K., &Shi, H*. (2024). A Robust Integrated Multi-Strategy Bus Control System via Deep Reinforcement Learning.Engineering Applications of Artificial Intelligence, 133, 107986. (SCI, JIF: 7.5, Q1)
9.Long, K.,Shi, H*., Chen, Z., Liang, Z., Li, X*., & de Souza, F. (2023). Bi-scale Car-following Model Calibration for Corridor Based on Trajectory.Transportation Research Part E: Logistics and Transportation Review, 186, 103497. (SCI, JIF: 8.3, Q1)
10.Liu, H.,Shi, H*., Yuan, T., Fu, S., & Ran, B. (2024). Bus Travel Feature Inference with Small Samples Based on Multi-clustering Topic Model over Internet of Things.Future Generation Computer Systems, 163, 107525. (SCI, JIF: 6.2, Q1)
11.Long, K., Sheng, Z.,Shi, H*., Li, X*., Chen, S., & Ahn, S. (2025). Physical enhanced residual learning (PERL) framework for vehicle trajectory prediction.Communications in Transportation Research, 5, 100166. (SCI, JIF: 12.5, Q1)
12.Ma, K.,Shi, H*., Li, X., Ma, C., & Huang, Z*. (2025). Development, Calibration, and Validation of a Novel Nonlinear Car-Following Model: Multivariate Piecewise Linear Approach for Adaptive Cruise Control Vehicles.Transportation Research Part E: Logistics and Transportation Review, 186, 103498. (SCI, JIF: 8.3, Q1)
13.Di, Y., Zhang, W., Ding, H*., Zheng, X., &Shi, H*. (2025). The expressway network design problem for multiple urban subregions based on macroscopic fundamental diagram.Computer-Aided Civil and Infrastructure Engineering, 40(2), 123–140. (SCI, JIF: 8.5, Q1)
14.Shi, H., Shi, K., Yue, X., Li, W., Zhou, Y*., & Ran, B. (2025). A Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition.IEEE Internet of Things Journal, 12(3), 4567–4578. (SCI, JIF: 8.2, Q1)
15.Li, Z., Bao, Z., Meng, H.,Shi, H*., Li, Q*., Yao, H., & Li, X. (2025). Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs.Communications in Transportation Research(SCI, JIF: 14.5, Q1)
16.You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z.,Shi, H*et al. (2024). FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction. Accepted byCommunications in Transportation Research(SCI, JIF: 14.5, Q1)
17.Di, Y., Zhang, W., Ding, H*.,Shi, H*., You, J., Li, H., & Ran, B. (2025). A Cooperation Control for Multiple Urban Regions Traffic Flow Coupled With an Expressway Network.IEEE Transactions on Network Science and Engineering. (SCI, JIF: 7.9, Q1)
18. Gan, R.,Shi, H*., Li, P*., Wu, K., An, B., Li, L., ... & Ran, B. (2025). Goal-based Neural Physics Vehicle Trajectory Prediction Model.Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)
19.Wu, K., Zhou, Y*., Shi, H*., Lord, D., Ran, B., & Ye, X. (2025). Hypergraph-based motion generation with multi-modal interaction relational reasoning.Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)
20.You, J.,Shi, H*., Jiang, Z., Huang, Z., Gan, R., Wu, K., ... & Ran, B. (2026).V2x-vlm: End-to-end v2x cooperative autonomous driving through large vision-language models. Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)