Haotian Shi

Haotian Shi

Associate Professor (Tenured) at Tongji University

Publications

You can also find my latest publications on my Google Scholar profile.

Published Journal Articles

(* corresponding author; ‡ co‑first author)

  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. Tian, K‡., Shi, H‡., Zhou, Y., & Ran, B. (2025). Physically Analyzable AI based Nonlinear Traffic Dynamics Modeling During Traffic Oscillation: A Koopman Approach. IEEE Transactions on Intelligent Transportation Systems, 26(4), 7890–7902. (SCI, JIF: 7.9, Q1)

  16. 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. Accepted by *Communications in Transportation Research (SCI, JIF: 14.5, Q1)

  17. 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 by *Communications in Transportation Research (SCI, JIF: 14.5, Q1)

  18. Wang, J., Dong, J., Shi, H*., Sundaram, S., Labi, S., Chen, S*. Reinforcement Learning Based Mobile Energy Disseminator Dispatching for On‑Road Electric Vehicle Charging. *Multimodal Transportation. (SCI, JIF: 8, Q1)

  19. Liu, H., Wu, K., Fu, S., Shi, H*., & Xu, H. (2023). Predictive Analysis of Vehicular Lane Changes: An Integrated LSTM Approach. *Applied Sciences, 13(18), 10157. (SCI, JIF: 2.8, Q2)

  20. 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)

  21. Gan, R., Shi, H*., Li, P*., Wu, K., An, B., Li, L., … & Ran, B. (2024). Goal‑based Neural Physics Vehicle Trajectory Prediction Model. *Transportation Research Part C: Emerging Technologies. (SCI, JIF: 7.9, Q1)

  22. Long, K., Ma, C., Li, H, Li, Z., Huang, H., Shi, H., … & Li, X. (2025). AI‑Enabled Digital Twin Framework for Safe and Sustainable Intelligent Transportation. Sustainability, 17(10), 4391. (SCI, JIF: 3.3, Q2)

  23. Shi, K., Wu, Y., Shi, H., Zhou, Y., & Ran, B. (2022). An integrated car‑following and lane changing vehicle trajectory prediction algorithm based on a deep neural network. Physica A: Statistical Mechanics and its Applications, 599, 127303. (SCI, JIF: 2.8, Q2)

  24. Liu, C., Sheng, Z., Chen, S., Shi, H., & Ran, B. (2023). Longitudinal control of connected and automated vehicles among signalized intersections in mixed traffic flow with deep reinforcement learning approach. Physica A: Statistical Mechanics and its Applications. (SCI, JIF: 2.8, Q2)

  25. Wu, R., Li, L., Shi, H., Rui, Y., Ngoduy, D., & Ran, B. (2024). Integrated driving risk surrogate model and car‑following behavior for freeway risk assessment. Accident Analysis & Prevention, 201, 107571. (SCI, JIF: 5.7, Q1)

  26. Yue, X., Shi, H., Zhou, Y., & Li, Z. (2024). Hybrid car‑following control for CAVs: Integrating linear feedback and deep reinforcement learning to stabilize mixed traffic. Transportation Research Part C: Emerging Technologies, 167, 104773. (SCI, JIF: 7.6, Q1)

  27. Long, K., Liang, Z., Shi, H., Chen, S., & Li, X. (2024). Traffic Oscillations Mitigation With Physics Enhanced Residual Learning (PERL)‑Based Predictive Control. Communications in Transportation Research. (SCI, JIF: 12.5, Q1)

  28. Wu, Z., Chen, T., Xie, H., Shi, H., Yang, Z., & Zhao, H. (2019). Optimization of Valve Strategy for High Compression‑Ratio Gasoline Engine Operating with Miller Cycle. Journal of Combustion Science and Technology, 25(4), 331–339. (EI, JIF: 1.7, Q3)

  29. Dong, H., Shi, H., Wang, G., & Zhao, F. (2012). Skillful use of technology to ensure equipment shape and position tolerance requirements. Journal of Ordnance Equipment Engineering, 33(12), 49–50. (中文核心期刊)

Conference Proceedings & Presentations

  1. Chen, T., Shi, H*., Vorhes, G., Parker, S. T., & Noyce, D. A. (2022). How to Collect Tribal Crash Data Properly? Experience from a New Wisconsin Crash Reporting System. ASCE International Conference on Transportation and Development 2022 (pp. 48‑60). (Conference Proceedings)

  2. Zhou H., Huang H*., Zhang P., Li X*., Shi H*, Long K. Online Physical Enhanced Residual Learning for Connected Autonomous Vehicles Platoon Centralized Control. IEEE Intelligent Vehicles Symposium 2024. arXiv preprint arXiv:2402.11468.

  3. Ma, C., Zhou, H., Zhang, P., Ma, K., Shi, H, Li, X. Safety Assurance Adaptive Control in Automated Vehicles: A Case Study on Modular Vehicles. 104 st Annual Meeting of the Transportation Research Board, Washington.

  4. Zhang, P., Zhou, H., Huang, H., Shi, H, Long, K., Li, X. Online Adaptive Platoon Control for Connected and Automated Vehicles via Physical Enhanced Residual Learning. 104 st Annual Meeting of the Transportation Research Board, Washington.

  5. You, J., Shi, H*., Wu, K., Long, K., Fu, S., Chen, S*., Ran, B. Crossfusor: A Cross‑Attention Transformer Enhanced Conditional Diffusion Model for Car‑Following Trajectory Prediction. 104 st Annual Meeting of the Transportation Research Board, Washington.

  6. Ma, K., Zhou, H., Zhang, Y., Shi, H, Ma, C., Li, Z., Zhang, P., Liang, Z., Li, X. Automated Vehicle Longitudinal Stability Analysis: Controller Design and Field Test. 104 st Annual Meeting of the Transportation Research Board, Washington.

  7. Long, K., Shi, H, Zhou, Y., Li, X. Physics Enhanced Residual Policy Learning (PERPL) for Safety Cruising in mixed traffic platooning under actuator and communication delay. 104 st Annual Meeting of the Transportation Research Board, Washington.

  8. Long, K., Shi, H, Liu, J., Li, X. VLM‑MPC: Vision Language Foundation Model (VLM)‑Guided Model Predictive Controller (MPC) for Autonomous Driving. 104 st Annual Meeting of the Transportation Research Board, Washington.

  9. Ma, K., Zhou, H., Shi, H, Ma, C., Li, X. Understanding Autonomous Vehicle Behavior: A Soft‑Margin Approach in Piecewise Linear Model. 104 st Annual Meeting of the Transportation Research Board, Washington.

  10. Gan R., Shi, H*., Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., Ran, B. Goal‑based Neural Physics Vehicle Trajectory Prediction Model. 104 st Annual Meeting of the Transportation Research Board, Washington.

  11. You, J., Shi, H*., Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li X., Ran, B. V2X‑VLM: End‑to‑End V2X Cooperative Autonomous Driving Through Large Vision‑Language Models. 104 st Annual Meeting of the Transportation Research Board, Washington.

  12. Huo, J., Liang, Z., Shi, H*., Ma, K., Li, X., Liu, Z. Vehicle Trajectory Tracking On Snowy Roads: A Model Predictive Control Method. 104 st Annual Meeting of the Transportation Research Board, Washington.

  13. Wu, K., Shi, H*., Zhou, Y*., Ran, B. HYPERGRAPH‑BASED MOTION GENERATION AND PLANNING WITH MULTI‑MODAL INTERACTION RELATIONAL REASONING. 104 st Annual Meeting of the Transportation Research Board, Washington.

  14. Long, K., Liang, Z., Shi, H, Shi, L., Chen, S., Li, X. Traffic Oscillations Mitigation With Physics Enhanced Residual Learning (PERL)-Based Predictive Control. 104 st Annual Meeting of the Transportation Research Board, Washington.

  15. Li, Z., Bao, Z., Meng, H., Shi, H*., Li Q., Yao, H., Li X. Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs. 104 st Annual Meeting of the Transportation Research Board, Washington.

  16. Tian, K#., Shi, H#., Zhou Y., Li, S. Physically Analyzable AI-Based Nonlinear Platoon Dynamics Modeling During Traffic Oscillation: A Koopman Approach. 104 st Annual Meeting of the Transportation Research Board, Washington.

  17. Di Y., Shi, H*., Zhang, W., Ding, H., Zheng X., Ran, B. Cooperative Route Guidance and Flow Control for Mixed Road Networks Comprising Expressway and Arterial Network. 104 st Annual Meeting of the Transportation Research Board, Washington.

  18. Di Y., Zhang W., Shi, H*., Ding H., Huo J., Ran, B. The Expressway Network Design Problem for Multiple Urban Subregions Based on the Macroscopic Fundamental Diagram. 104 st Annual Meeting of the Transportation Research Board, Washington.

  19. Di, Y., Zhang, W., You, J., Shi, H*., Li, H., Ding, H., Ran, B. A Cooperative Flow Control for Multiple Urban Regions Coupled with an Expressway Network. 104 st Annual Meeting of the Transportation Research Board, Washington.

  20. Long, K., Shi, H*, Sheng Z., Li, X*., Chen, S. ASCE International Conference on Transportation and Development 2024.

  21. Shi, H, Dong, S., Wu, Y., Li, S., Zhou, Y., Ran, B. (2024). Generative Adversarial Network for Car Following Trajectory Generation and Anomaly Detection. Presented at 103 st Annual Meeting of the Transportation Research Board, Washington. (Poster).

  22. Wu K., Zhou Y., Shi, H*., Li X., Ran B. (2024). Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional Networks. Presented at 103 st Annual Meeting of the Transportation Research Board, Washington. (Poster).

  23. Long K., Sheng Z., Shi, H*., Li X*., Chen S., Ahn S. (2024). A Physics Enhanced Residual Learning (PERL) Framework for Vehicle Trajectory Prediction. Presented at 103 st Annual Meeting of the Transportation Research Board, Washington. (Poster).

  24. Long K., Shi, H*., Chen Z., Liang Z., Li X*., Souza F. (2024). Bi-scale Car-following Model Calibration for Corridor Based on Trajectory. Presented at 103 st Annual Meeting of the Transportation Research Board, Washington. (Poster).

  25. Ma K., Li X., Shi, H, Ma C., Huang Z., Ghiasi A., Wang Q., Hourdos J., McHale G. A Novel Non-linear Car-following Model for Automated Vehicle: Development, Calibration, and Validation. Presented at 103 st Annual Meeting of the Transportation Research Board, Washington. (Poster).

  26. Shi, H. (2023). Mixed Platoon Control Strategy of Connected Automated Vehicles based on Physics-informed Deep Reinforcement Learning. INFORMS 2023. (Panel Speaker).

  27. Shi, H. (2023). Mixed Platoon Control Strategy of Connected and Automated Vehicles Based on Physics-Informed Deep Reinforcement Learning. Young Faculty & Practitioner Workshop. ASCE International Conference on Transportation and Development 2023. 2438399. (Panel Speaker).

  28. Chen T., Shi, H*, Parker, S. T., Vorhes, G., & Noyce, D. A. (2023). Conceptual Development for a Generalized Tribal Crash Safety Dashboard. ASCE International Conference on Transportation and Development 2023. 2252954. (Poster).

  29. Chen T., Shi, H*, Parker, S. T., Vorhes, G., & Noyce, D. A. (2023). Conceptual Development for a Generalized Tribal Crash Safety Dashboard. 102 st Annual Meeting of the Transportation Research Board, Washington, D.C., 2023. TRBAM-23-02333. (Podium).

  30. Shi, H, Chen, D., Zheng, N., Wang, X., Zhou, Y., & Ran, B. (2023). Distributed Connected Automated Vehicles Control under Real-time Aggregated Macroscopic Car-following Behavior Estimation based on Deep Reinforcement Learning. 102 st Annual Meeting of the Transportation Research Board, Washington, D.C., 2023. TRBAM-23-02403. (Poster).

  31. Chen T., Shi, H*, Vorhes G., Parker, S. T., Noyce, D. A. Tribal Crash Reporting System Improvements in Wisconsin. Presented at 101 st Annual Meeting of the Transportation Research Board, Washington, D.C., 2022. TRBAM-22-02539. (Podium).

  32. Shi, H, Nie, Q., Fu, S., Wang, X., Zhou, Y., & Ran, B. A Distributed Deep Reinforcement Learning Based Integrated Dynamic Bus Control System in a Connected Environment. Presented at 101 st Annual Meeting of the Transportation Research Board, Washington, D.C., 2022. TRBAM-22-00882. (Poster).

  33. Chen, T., Shi, H, Vorhes, G., Parker, S. T., & Noyce, D. A. Data and System Architecture Improvements for Statewide Crash Mapping and Analysis. Presented at 99 th Annual Meeting of the Transportation Research Board, Washington, D.C., 2020. 20-05109. (Poster).

  34. Shi, H, Zhou, Y., Wu, K., Wang, X., Lin, Y., & Ran, B. Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment. ASCE T&DI Technical Committee on Artificial Intelligence Student Competition. 2021. (Top 10 in Competition).

Granted Invention Patents

  1. Ran B., Cheng Y., Chen T., Yao Y., Wu K., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Autonomous Vehicle and Cloud Control (AVCC) System with Roadside Unit (RSU) Network: U.S. Patent Application 17/840,249 [P].

  2. Ran B., Li S., Cheng Y., Chen T., Dong S., Shi K, Shi H, Li X. Distributed driving systems and methods for automated vehicles: U.S. Patent Application 16/996,684 [P]. 2021.

  3. Ran B., Chen T., Dong S., Cheng Y., Zhang M., Li X., Li S., Shi K, Shi H, Yao Y., Mo Y., Liu H., Wu K., Yi R. Function allocation for automated driving systems: U.S. Patent Application 17/328,625 [P]. 2024.

  4. Ran B., Cheng Y., Chen T., Yao Y., Wu K., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Autonomous Vehicle and Cloud Control System: 17/840,237 [P]. 2024.

  5. Ran B., Cheng Y., Chen T., Yao Y., Wu K., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Autonomous Vehicle (AV) Control System with Roadside Unit (RSU) Network: U.S. Patent Application 17/840,243 [P]. 2024.

  6. Ran B., Mao P., Lu W., Yi Z., Li L., Cheng Y., Xu L., Zheng Y., Chen T., Shi H, Wu K. Function allocation for automated driving systems: U.S. Patent Application 17/499,283 [P]. 2024.

  7. Ran B., Cheng Y., Li S., Tian K., Chen T., Dong S., Shi K, Shi H, Li X. Distributed driving with flexible roadside resources: U.S. Patent Application 12,046,136 [P]. 2024.

  8. Ran B., Zheng Y., Wang C., Cheng Y., Yao Y., Wu K., Chen T., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Autonomous vehicle cloud system: U.S. Patent Application 18/227,541 [P]. 2025.

  9. Ran B., Liang B., Zhao Y., Cheng Y., Yao Y., Wu K., Chen T., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Autonomous Vehicle Intelligent System (AVIS). U.S. Patent Application 18/227,548 [P]. 2025.

  10. ROADSIDE EDGE COMPUTING SYSTEM FOR AUTONOMOUS VEHICLES. Ran B., An B., Zhou Z., Li M., Wu K., Cheng Y., Yao Y., Shi H, Chen T., Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. U.S. Patent Application 18/733,475 [P]. 2025.

  11. Ran B., Shi K, Lu W., Cheng Y., Zhang H., Shi H, Chen T., Liang B., Yao Y., Wu K., Fu S. Connected Reference Marker System: U.S. Patent Application 63/210,845 [P]. 2025.

  12. Ran B., Wang Z., Wu R., Jiang J., Cheng Y., Wu K., Yao Y., Chen T., Shi H, Li S., Shi K, Zhang Z., Ding F., Tan H., Wu Y., Dong S., Ye L., Li X. Vehicle AI Computing System (VACS) for Autonomous Driving. U.S. Patent Application 18/742,133 [P]. 2025.

  13. Ran B., Zhao K., Li H., Zhang M., Li S., Cheng Y., Chen Z., Ye J., Dong S., Shi H. Vehicle Intelligent Unit: U.S. Patent Application 63/175,158 [P]. 2025.

  14. Chen T., Ran B., Dong S., Wu K., Cheng Y., Li L., Li S., Li X., Mo Y., Yao Y., Shi K, Shi H, Li H. Systematic Intelligent System: U.S. Patent Application 17/537,593 [P]. 2025.

  15. Ran B., Dong S., Cheng Y., Chen T., Li S., Li X., Shi K, Shi H, Wu K., Yao Y., Yi R. Device allocation system: U.S. Patent Application 17/192,441 [P]. 2025.

  16. Shi H & Liang X. A kind of AMT clutch friction plate rapid wear test system and method: CN Patent Application CN 105606362B. 2019.

  17. Shi H, Wu Z., Zhang J., Han Y., Lan S., & Liang X. AMT clutch plate rapid wear testing system: CN Patent Application CN 205449493U. 2016.

  18. Shi H, Wu Z., Han Y., Zhang J., Lan S., & Liang X. Automobile suspension system vibration energy recovering apparatus. CN 105252987A.

  19. Shi H, Wu Z., Lan S., Han Y., Zhang J., & Liang X. Vehicle shock absorber vibration energy recovery unit: CN Patent Application CN 205123547U. 2016.

  20. Shi H, Wu Z., Lan S., Zhang J., Han Y., & Liang X. A kind of vehicle shock absorber vibration energy recovery device: CN Patent Application CN105226910A. 2016.

  21. Shi H, Wu Z., Lan S., Zhang J., Han Y., & Liang X. Car suspension system vibration energy recovery unit: CN Patent Application CN205112909U. 2016.

  22. Ran B., Zhao K., Li H., Zhang M., Chen Z., Jiang J., Wu R., Zhang W., He S., Li S., Cheng Y., Shi H. Vehicle-mounted intelligent unit with fusion perception and collaborative decision function and control method: CN Patent Application CN 113954879B. 2023.

  23. Nie Q., Zhang H., Ou J., Pjing, Yue P., Zhou Y., Shi H, Xiao X. Multi-strategy fusion control method for bus operation in intelligent network environment. CN115691196A. 2023.

  24. Ran B., Li S., Cheng Y., Chen T., Dong S., Shi K, Shi H, Li X. Distributed driving system and method for automatically driving vehicle: CN Patent Application CN 114585876B. 2023.

  25. Li S., Ran B., Cheng Y., Chen Z., He S., Rui Y., Li R., Gu H., Li L., Chen T., Li X., Dong S., Shi K, Shi H, Yao Y., Wu K., Zhang X. Intelligent roadside tool box: CN Patent Application CN 113496602B. 2023.

  26. Ran B., Liang B., Lu W., Yi X., Rui Y., Kong L., Gong Y., Shi K, Shi H, Cheng Y., Chen T., He S., Yao Y., Wu K., Fu S. Virtual road configuration module: CN Patent Application CN114664116B. 2023.

  27. Chen T., Shi H, and Yao Z. Gasoline engine starting method combining variable oil injection strategy with waste gas energy utilization: CN Patent Application CN 111550322B. 2022.

  28. Chen T., Yao Z., Shi H. Method for improving cold start combustion of gasoline engine with variable residual waste gas rate: CN Patent Application CN 111550315B. 2022.

  29. Ran B., Chen T., Li S., Cheng Y., Li L., Zhou Z., He S., Li X., Dong S., Yao Y., Shi K, Shi H, Wu K., Fu S. Collaborative autopilot system. CN 117087695A. 2023.

Standard Guidelines

  1. Guideline for the Development of Five Versions of Collaborative Automated Driving (CAD) Systems (车路协同自动驾驶系统版本建设指南).

  2. Study Report on Technical Development Roadmaps for Collaborative Automated Driving (车路协同自动驾驶技术发展路线图研究报告).