Zhong Cao

Zhong Cao

University of Michigan

Publications

2023

  1. Cao, Z., Jiang, K., Zhou, W., Xu, S., Peng, H., & Yang, D. (2023). Continuous improvement of self-driving cars using dynamic confidence-aware reinforcement learning. Nature Machine Intelligence, 5(2), 145–158. https://doi.org/10.1038/s42256-023-00610-y[pdf]
  2. Cao, Z., Li, X., Jiang, K., Zhou, W., Liu, X., Deng, N., & Yang, D. (2023). Autonomous Driving Policy Continual Learning with One-Shot Disengagement Case. IEEE Transactions on Intelligent Vehicles, 8(2), 1380–1391. https://doi.org/10.1109/tiv.2022.3184729
  3. Zhou, W., Cao, Z.*, Deng, N., Jiang, K., & Yang, D. (2023). Identify, Estimate and Bound the Uncertainty of Reinforcement Learning for Autonomous Driving. IEEE Transactions on Intelligent Transportation Systems, 24(8), 7932–7942. https://doi.org/10.1109/tits.2023.3266885
  4. Liu, J., Wang, H., Cao, Z.*, Yu, W., Zhao, C., Zhao, D., Yang, D., & Li, J. (2023). Semantic Traffic Law Adaptive Decision-Making for Self-Driving Vehicles. IEEE Transactions on Intelligent Transportation Systems, 1–15. https://doi.org/10.1109/tits.2023.3294579
  5. Zhou, W., Cao, Z.*, Deng, N., Liu, X., Jiang, K., & Yang, D. (2023). Dynamically Conservative Self-Driving Planner for Long-Tail Cases. IEEE Transactions on Intelligent Transportation Systems, 24(3), 3476–3488. https://doi.org/10.1109/tits.2022.3225538
  6. Jiao, X., Chen, J., Jiang, K., Cao, Z., & Yang, D. (2023). Autonomous Driving Risk Assessment with Boundary-based Environment Model. IEEE Transactions on Intelligent Vehicles, 1–15. https://doi.org/10.1109/tiv.2023.3285762
  7. Jiao, X., Chen, J., Jiang, K., Wang, Y., Cao, Z., Yang, M., & Yang, D. (2023). Reliable Autonomous Driving Environment Model with Unified State-Extended Boundary. IEEE Transactions on Intelligent Transportation Systems, 24(1), 516–527. https://doi.org/10.1109/tits.2022.3216774
  8. Qian, Z., Jiang, K., Zhou, W., Wen, J., Jing, C., Cao, Z.*, Yang, D. (2023) An End-To-End Autonomous Driving Pre-Trained Transformer Model for Multi-Behavior-Optimal Trajectory Generation, 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
  9. Liu, X., Cao, Z., Li, X., Yang, Y., Jiang, K., & Yang, D. (2023, August). Acceleration Method for Hazardous Scenario Generation Based on Disengagement Cases. CICTP 2023. https://doi.org/10.1061/9780784484869.252

2022

  1. Cao, Z., Xu, S., Jiao, X., Peng, H., & Yang, D. (2022). Trustworthy safety improvement for autonomous driving using reinforcement learning. Transportation Research Part C: Emerging Technologies, 138, 103656. https://doi.org/10.1016/j.trc.2022.103656
  2. Cao, Z., Xu, S., Peng, H., Yang, D., & Zidek, R. (2022). Confidence-Aware Reinforcement Learning for Self-Driving Cars. IEEE Transactions on Intelligent Transportation Systems, 23(7), 7419–7430. https://doi.org/10.1109/tits.2021.3069497
  3. Cao, Z., Yang, D., Jiang, K., & Xu, S. (2022). Monocular Connected-Vehicle Position Estimation on Sloping and Uneven Roads. IEEE Intelligent Transportation Systems Magazine, 14(1), 228–241. https://doi.org/10.1109/mits.2020.2985062
  4. Liu, J., Wang, H., Peng, L., Cao, Z.*, Yang, D., & Li, J. (2022). PNNUAD: Perception Neural Networks Uncertainty Aware Decision-Making for Autonomous Vehicle. IEEE Transactions on Intelligent Transportation Systems, 23(12), 24355–24368. https://doi.org/10.1109/tits.2022.3197602
  5. Jiao, X., Cao, Z., Chen, J., Jiang, K., & Yang, D. (2022). A General Autonomous Driving Planner Adaptive to Scenario Characteristics. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21228-21240. https://doi.org/10.1109/TITS.2022.3185491
  6. Xu, S., Zidek, R., Cao, Z., Lu, P., Wang, X., Li, B., & Peng, H. (2022). System and Experiments of Model-Driven Motion Planning and Control for Autonomous Vehicles. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(9), 5975–5988. https://doi.org/10.1109/tsmc.2021.3131141
  7. Zhou, W., Cao, Z.*, Xu, Y., Deng, N., Liu, X., Jiang, K., & Yang, D. (2022, October). Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). https://doi.org/10.1109/itsc55140.2022.9921749
  8. Lin, J., Zhou, W., Wang, H., Cao, Z.*, Yu, W., Zhao, C., Zhao, D., Yang, D., & Li, J. (2022, October). Road Traffic Law Adaptive Decision-making for Self-Driving Vehicles. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC). https://doi.org/10.1109/itsc55140.2022.9922208

2021

  1. Cao, Z., Yang, D., Xu, S., Peng, H., Li, B., Feng, S., & Zhao, D. (2021). Highway Exiting Planner for Automated Vehicles Using Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 22(2), 990–1000. https://doi.org/10.1109/tits.2019.2961739
  2. Cao, Z., Liu, J., Zhou, W., Jiao, X., & Yang, D. (2021, July). LiDAR-based Object Detection Failure Tolerated Autonomous Driving Planning System. 2021 IEEE Intelligent Vehicles Symposium (IV). https://doi.org/10.1109/iv48863.2021.9575925
  3. Deng, N., Cao, Z., Zhou, W., Jiang, K., & Yang, D. (2021, September). Adapt the Driving Policy to Local Traffic before Entering the New Area. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC). https://doi.org/10.1109/itsc48978.2021.9564711
  4. Deng, N., Jiang, K., Cao, Z., Zhou, W., & Yang, D. (2021, December). Decision-Oriented Driving Scenario Recognition Based on Unsupervised Learning. CICTP 2021. https://doi.org/10.1061/9780784483565.055

2020

  1. Zhong, Y.+, Cao, Z.+, Zhu, M., Wang, X., Yang, D., & Peng, H. (2020, October). CLAP: Cloud-and-Learning-compatible Autonomous driving Platform. 2020 IEEE Intelligent Vehicles Symposium (IV). https://doi.org/10.1109/iv47402.2020.9304828
  2. Zhu, M., Ghaffari, M., Zhong, Y., Lu, P., Cao, Z., Eustice, R. M., & Peng, H. (2020, October). Monocular Depth Prediction through Continuous 3D Loss. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros45743.2020.9341767
  3. Zhou, W., Jiang, K., Cao, Z., Deng, N., & Yang, D. (2020, September). Integrating Deep Reinforcement Learning with Optimal Trajectory Planner for Automated Driving. 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC). https://doi.org/10.1109/itsc45102.2020.9294275

2019

  1. Cao, Z., Yang, D., Jiang, K., Xu, S., Wang, S., Zhu, M., & Xiao, Z. (2019). A Geometry-driven Car-following Distance Estimation Algorithm Robust to Road Slopes. Transportation Research Part C: Emerging Technologies, 102, 274–288. https://doi.org/10.1016/j.trc.2019.03.009
  2. Feng, S., Zhang, Y., Li, S. E., Cao, Z., Liu, H. X., & Li, L. (2019). String stability for vehicular platoon control: Definitions and analysis methods. Annual Reviews in Control, 47, 81–97. https://doi.org/10.1016/j.arcontrol.2019.03.001
  3. Yang, D., Jiao, X., Jiang, K., & Cao, Z. (2019). Driving Space for Autonomous Vehicles. Automotive Innovation, 2(4), 241–253. https://doi.org/10.1007/s42154-019-00081-1

2018

  1. Yang, D., Jiang, K., Zhao, D., Yu, C., Cao, Z., Xie, S., Xiao, Z., Jiao, X., Wang, S., & Zhang, K. (2018). Intelligent and connected vehicles: Current status and future perspectives. Science China Technological Sciences, 61(10), 1446–1471. https://doi.org/10.1007/s11431-017-9338-1
  2. Cao, Z., Yang, D., Jiang, K., Wang, T., Jiao, X., & Xiao, Z. (2018). End-to-End Adaptive Cruise Control Based on Timing Network. In Lecture Notes in Electrical Engineering (pp. 839–852). Springer Singapore. https://doi.org/10.1007/978-981-10-8506-2_56

2017

  1. Liu, C., Jiang, K., Xiao, Z., Cao, Z., & Yang, D. (2017, October). Lane-level route planning based on a multi-layer map model. 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). https://doi.org/10.1109/itsc.2017.8317681