👨‍🎓 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. Currently, I am a visiting scholar at the Next Generation Mobility Systems Lab at the University of Michigan, Ann Arbor, under the guidance of Dr. Neda Masoud.

I earned my Bachelor’s degree in Engineering from the School of Traffic and Transportation Engineering at Central South University in 2021.

My research focuses on decision-making of CAVs, wheeled robot decision-making and control, Human-centric AI, and efficient RL algorithms.

🔥 News

• [2025.02] Reachability-Aware Reinforcement Learning for Collision Avoidance in Human-Machine Shared Control has been preprinted. You can contact us via email to obtain the real vehicle data related with this study and the right to use it freely.
• [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!

• [2024.12] We have open-sourced a project using Simulink as a bridge for CarSim and Python co-simulation. We invite researchers to improve it and develop RL algorithms for real vehicles.
• [2024.11] High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles has been preprinted and we provides a very interesting video (https://www.youtube.com/watch?v=5wp67FcpfL8).
• [2024.11] Tire-Road friction coefficients adaptive estimation through image and vehicle dynamics integration has been accepted in MSSP Journal.

📝 Publications

Journal Papers （Provide original text whenever possible）

• 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.

• Zhao S, Zhang J, Masoud N, et al. Reachability-Aware Reinforcement Learning for Collision Avoidance in Human-Machine Shared Control[J]. arXiv preprint arXiv:2502.10610, 2025.

• Zhao S, Zhang J, Masoud N, et al. High-Speed Cornering Control and Real-Vehicle Deployment for Autonomous Electric Vehicles[J]. arXiv preprint arXiv:2411.11762, 2024.

• 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.

• 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.

• 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.

• 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.

• 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.

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

• 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.

📖 Educations

• 2024.10 - Present, 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

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 visit the team homepage or contact us by email. All emails for academic discussions will be replied within 24 hours.