👨‍🎓 About Me

Hello! My name is Shiyue Zhao, and I am a PhD student at the School of Vehicle and Mobility of Tsinghua University under the supervision of Prof. Junzhi Zhang.

I earned my Bachelor’s degree in Engineering from the School of Traffic and Transportation Engineering at Central South University in 2021. From October 2024 to 2025, I was a visiting scholar at the Next Generation Mobility Systems Lab at the University of Michigan, Ann Arbor, under the guidance of Dr. Neda Masoud.

My research focuses on decision-making for CAVs, driving VLA systems, wheeled robot decision-making and control, human-centered AI, and efficient RL algorithms.

🔥 News

• [2026.05] We released the Extreme Driving Dataset, a multi-modal driving dataset with rich chassis dynamics (raw IMU and GPS heading) for limit-handling research and VLA model training. It covers six driving scenario categories: Normal, Complex Traffic, Critical, Low Light, Rain, and Snow.
  Project Page: https://sean-shiyuez.github.io/extreme-driving-dataset-web/
  Dataset: https://huggingface.co/datasets/Stary108/Extreme_Driving_Conditions_Dataset
• [2026.04] Our paper “Behaviorally informed joint optimization of charger placement and dynamic spatio-temporal pricing for electric vehicle networks” co-authored with University of Michigan (Iason Liagkas, Neda Masoud) has been published!
• [2026.03] Our paper “Human-machine shared driving for vehicle collision avoidance based on Hamilton-Jacobi reachability” has been accepted by Accident Analysis & Prevention! You can contact us via email to obtain the real vehicle data related with this study and the right to use it freely.
• [2025.04] High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles has been accepted by IEEE Transactions on Industrial Electronics, and we provide a very interesting video (https://www.youtube.com/watch?v=5wp67FcpfL8).
• [2025.01] The road surface image dataset associated with the paper “Tire-Road Friction Coefficients Adaptive Estimation through Image and Vehicle Dynamics Integration” is now publicly available and researchers are welcome to access it.
• [2024.12] We release our Python-based high-accuracy vehicle dynamic model with a validated high-fidelity tire simulation, designed for both conventional and drift driving scenarios!

💻 Open Source Code

• Extreme Driving Dataset — A multi-modal driving dataset with chassis dynamics for limit-handling research and VLA model training. [Dataset on Hugging Face]

• High-Accuracy Vehicle Dynamic Model — A Python-based vehicle dynamics model with validated high-fidelity tire simulation for conventional and drift-driving scenarios.

• CarSim-Python RL Co-simulation — A Simulink bridge for CarSim and Python co-simulation, designed to support reinforcement learning research for real vehicles.

• Extreme Road Image Dataset — Road surface images for tire-road friction coefficient estimation research.

📝 Publications

Journal Papers （Provide original text whenever possible）

• Iason Liagkas, Shiyue Zhao, Neda Masoud. “Behaviorally informed joint optimization of charger placement and dynamic spatio-temporal pricing for electric vehicle networks”. Transportation Research Part B: Methodological, 2026.

• Shiyue Zhao, Junzhi Zhang, Rui Zhou, Neda Masoud, Jianxiong Li, Helai Huang, Shijie Zhao. “Human-machine shared driving for vehicle collision avoidance based on Hamilton-Jacobi reachability”. Accident Analysis & Prevention, 230 (2026): 108474. 📋 Cite

• Liu Q, Huang H, Zhao S, et al. RiskNet: interaction-aware risk forecasting for autonomous driving in long-tail scenarios[J]. Transportation Research Part E: Logistics and Transportation Review, 2026, 205: 104478.

• Zhao S, Zhang J, Jiang Y, et al. Tire-Road friction coefficients adaptive estimation through image and vehicle dynamics integration[J]. Mechanical Systems and Signal Processing, 2025, 224: 112039. 📋 Cite

• Zhao S, Zhang J, Masoud N, et al. High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles[J]. IEEE Transactions on Industrial Electronics, 2025. 📋 Cite

• Zhao S, Zhang J, He C, et al. Autonomous vehicle extreme control for emergency collision avoidance via Reachability-Guided reinforcement learning[J]. Advanced Engineering Informatics, 2024, 62: 102801. 📋 Cite

• Zhao S, Zhang J, He X, et al. A Harmonized Approach: Beyond-the-Limit Control for Autonomous Vehicles Balancing Performance and Safety in Unpredictable Environments[J]. IEEE Transactions on Intelligent Transportation Systems, 2024. 📋 Cite

• Zhao S, Zhang J, He C, et al. Adaptive drift control of autonomous electric vehicles after brake system failures[J]. IEEE Transactions on Industrial Electronics, 2023. 📋 Cite

• Zhao S, Zhang J, He C, et al. Collision-free emergency planning and control methods for CAVs considering intentions of surrounding vehicles[J]. ISA transactions, 2023, 136: 535-547. 📋 Cite

• Hou, X., Gan, M., Wu, W., Ji, Y., Zhao, S., and Chen, J. (2024). Cross-Observability Optimistic-Pessimistic Safe Reinforcement Learning for Interactive Motion Planning With Visual Occlusion. IEEE Transactions on Intelligent Transportation Systems.

• Hou, X., Gan, M., Wu, W., Ji, Y., Zhao, S., & Chen, J. (2024). Equipping With Cognition: Interactive Motion Planning Using Metacognitive-Attribution Inspired Reinforcement Learning for Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems.

• Hou, X., Gan, M., Wu, W., Zhao, S., Ji, Y., & Chen, J. (2024). Risk-Conscious Mutations in Jump-Start Reinforcement Learning for Autonomous Racing Policy. IEEE Transactions on Cybernetics.

• Zhou, Z., Huang, H., Li, B., Zhao, S., and Mu, Y. (2024). SafeDrive: Knowledge-and Data-Driven Risk-Sensitive Decision-Making for Autonomous Vehicles with Large Language Models. arXiv preprint arXiv:2412.13238.（Being considered for publication in IEEE TITS journal）

• Han, J., Zhang, J., Lv, C., He, C., Wei, H., Zhao, S., and Ji, Y. (2024). Safe Replanning and Motion Control for Automated Emergency Braking Under Braking System Failures. IEEE Transactions on Vehicular Technology.

• Han, J., Zhang, J., Lv, C., He, C., Wei, H., and Zhao, S. (2024). Robust Fault Tolerant Path Tracking Control for Intelligent Vehicle under Steering System Faults. IEEE Transactions on Intelligent Vehicles.

• Hou, X., Gan, M., Wu, W., Wang, C., Ji, Y., and Zhao, S. (2024). Merging planning in dense traffic scenarios using interactive safe reinforcement learning. Knowledge-Based Systems, 290, 111548.

• Han, J., Zhang, J., He, C., Lv, C., Wei, H., Zhang, J., and Zhao, S. (2024). Uniform Finite Time Safe Path Tracking Control for Obstacle Avoidance of Autonomous Vehicle via Barrier Function Approach. IEEE Transactions on Intelligent Transportation Systems.

• Huang, H., Liu, J., Shi, G., Zhao, S., Li, B., and Wang, J. (2024). Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Environments. arXiv preprint arXiv:2402.11467. （Being considered for publication in IEEE TITS journal）

• Hou, X., Gan, M., Zhang, J., Zhao, S., and Ji, Y. (2023). Vehicle ride comfort optimization in the post-braking phase using residual reinforcement learning. Advanced Engineering Informatics, 58, 102198.

• Hou, X., Gan, M., Zhang, J., Zhao, S., and Ji, Y. (2023). Secondary crash mitigation controller after rear-end collisions using reinforcement learning. Advanced engineering informatics, 58, 102176

Conference Proceedings

• Zhao, S., Song, Z., and He, X. (2023, October). A Finite-Time Safety Filter for Learning-Based Autonomous Driving. In 2023 IEEE International Conference on Unmanned Systems (ICUS) (pp. 1-6). IEEE. 📋 Cite

• Zhao, S., Li, J., Hu, X., Zhang, J., and He, C. (2022, November). Vehicle Extreme Control based on Offline Reinforcement Learning. In 2022 China Automation Congress (CAC) (pp. 4539-4543). IEEE. 📋 Cite

• Huang, H., Zheng, X., Liu, Y., Zhao, S., Wang, Y., and Wang, J. (2023, November). Intelligent Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Scenarios. In 2023 3rd International Conference on Digital Society and Intelligent Systems (DSInS) (pp. 258-264). IEEE.

@article{zhao2026shared,
  author  = {Zhao, Shiyue and Zhang, Junzhi and Zhou, Rui and Masoud, Neda and Li, Jianxiong and Huang, Helai and Zhao, Shijie},
  title   = {Human-machine shared driving for vehicle collision avoidance based on {Hamilton-Jacobi} reachability},
  journal = {Accident Analysis & Prevention},
  volume  = {230},
  pages   = {108474},
  year    = {2026}
}

@article{zhao2025mssp,
  author  = {Zhao, S. and Zhang, J. and Jiang, Y. and others},
  title   = {Tire-Road friction coefficients adaptive estimation through image and vehicle dynamics integration},
  journal = {Mechanical Systems and Signal Processing},
  volume  = {224},
  pages   = {112039},
  year    = {2025}
}

@article{zhao2025tie,
  author  = {Zhao, S. and Zhang, J. and Masoud, N. and others},
  title   = {High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles},
  journal = {IEEE Transactions on Industrial Electronics},
  year    = {2025}
}

@article{zhao2024aei,
  author  = {Zhao, S. and Zhang, J. and He, C. and others},
  title   = {Autonomous vehicle extreme control for emergency collision avoidance via {Reachability-Guided} reinforcement learning},
  journal = {Advanced Engineering Informatics},
  volume  = {62},
  pages   = {102801},
  year    = {2024}
}

@article{zhao2024tits,
  author  = {Zhao, S. and Zhang, J. and He, X. and others},
  title   = {A Harmonized Approach: Beyond-the-Limit Control for Autonomous Vehicles Balancing Performance and Safety in Unpredictable Environments},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  year    = {2024}
}

@article{zhao2023tie,
  author  = {Zhao, S. and Zhang, J. and He, C. and others},
  title   = {Adaptive drift control of autonomous electric vehicles after brake system failures},
  journal = {IEEE Transactions on Industrial Electronics},
  year    = {2023}
}

@article{zhao2023isa,
  author  = {Zhao, S. and Zhang, J. and He, C. and others},
  title   = {Collision-free emergency planning and control methods for {CAVs} considering intentions of surrounding vehicles},
  journal = {ISA Transactions},
  volume  = {136},
  pages   = {535--547},
  year    = {2023}
}

@inproceedings{zhao2023icus,
  author    = {Zhao, S. and Song, Z. and He, X.},
  title     = {A Finite-Time Safety Filter for Learning-Based Autonomous Driving},
  booktitle = {2023 IEEE International Conference on Unmanned Systems (ICUS)},
  pages     = {1--6},
  year      = {2023}
}

@inproceedings{zhao2022cac,
  author    = {Zhao, S. and Li, J. and Hu, X. and Zhang, J. and He, C.},
  title     = {Vehicle Extreme Control based on Offline Reinforcement Learning},
  booktitle = {2022 China Automation Congress (CAC)},
  pages     = {4539--4543},
  year      = {2022}
}

📖 Educations

• 2024.10 - 2025.09, Visiting Scholar, Next Generation Mobility Systems Lab, University of Michigan, Ann Arbor, USA.
• 2021.08 - Present, PhD candidate, School of Vehicle and Mobility, Tsinghua University, Beijing, China.
• 2017.08 - 2021.06, Undergraduate, School of Traffic & Transportation Engineering, Central South University, Changsha, China.

🧑‍🎨 Services

Reviewer for Journals:

• ISA Transactions
• IEEE Transactions on Industrial Electronics (TIE)
• Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
• Scientific Reports

Reviewer for conferences:

• Chinese Automation Congress (CAC)
• IEEE International Conference on Unmanned Systems (ICUS)

🤔 Team

Currently, our team is actively promoting the research of intelligent chassis under the leadership of Professor Zhang Junzhi. If you want to be involved in this process or have any questions about my/the team’s research, please contact us by email. I usually reply to academic discussion emails within 24 hours.