Journal

1. J. Duan, Y. Ren, F. Zhang, J. Li, S. E. Li, Y. Guan, and K. Li, “Encoding Distributional Soft Actor-Critic for Autonomous Driving in Multi-Lane Scenarios,” IEEE Computational Intelligence Magazine, 2023.     Download
2. Y. Qu, H. Chu, S. Gao, J. Guan, H. Yan, L. Xiao, S. E. Li, and J. Duan, “RL-driven MPPI: Accelerating Online Control Laws Calculation with Offline Policy,” IEEE Transactions on Intelligent Vehicles, 2023.     Download
3. J. Duan, J. Li, X. Chen, K. Zhao, S. E. Li, and L. Zhao, “Optimization Landscape of Policy Gradient Methods for Discrete-time Static Output Feedback,” IEEE Transactions on Cybernetics, 2023.     Download
4. J. Duan, Y. Kong, C. Jiao, Y. Guan, S. E. Li, C. Chen, B. Nie, and K. Li,“Decision-making under on-ramp merge scenarios by distributional soft actor-critic algorithm,” arXiv preprint arXiv:2103.04535, 2021.     Download
5. J. Duan, W. Cao, Y. Zheng, and L. Zhao, “On the Optimization Landscape of Dynamic Output Feedback Linear Quadratic Control,” IEEE Transactions on Automatic Control, 2023.     Download
6. D. Yu, W. Zou, Y. Yang, H. Ma, S. E. Li, J. Chen and J. Duan“Safe Model-Based Reinforcement Learning with an Uncertainty-Aware Reachability Certificate,” arXiv preprint arXiv:2210.07553, 2022.     Download
7. G. Ren, G. Zhan, L. Tang, S. E. Li, J. Jiang, K. Li, and J. Duan, “Improve generalization of driving policy at signalized intersections with adversarial learning,” vol. 152, pp. 104161–104161, Jul. 2023.    Download
8. 段京良, 陈良发, 王文轩, 焦春绚, 刘征宇, 马飞, 李升波. “智能汽车主动避撞工况的高实时预测控制” 汽车安全与节能学报, 2023, 14(5): 580-590.    Download
9. W. Wang, Y. Zhang, J. Gao, Y. Jiang, Y. Yang, Z. Zheng, W. Zou, J. Li, C. Zhang, W. Cao, G. Xie, J. Duan, S. E. Li, “GOPS: A general optimal control problem solver for autonomous driving and industrial control applications,” Communications in Transportation Research, vol. 3, p. 100096, Dec. 2023.
10. J. Li, S. E. Li, J. Duan, Y. Lyu, W. Zou, Y. Guan, Y. Yin, “Relaxed Policy Iteration Algorithm for Nonlinear Zero-Sum Games with Application to H-infinity Control,” pp. 1–8, Jan. 2023.    Download
11. J. Duan, J. Li, Q. Ge, S. E. Li, M. Bujarbaruah, F. Ma, D. Zhang, “Relaxed Actor-Critic With Convergence Guarantees for Continuous-Time Optimal Control of Nonlinear Systems,” vol. 8, no. 5, pp. 3299–3311, May 2023.    Download
12. Z. Lin, J. Ma, J. Duan, S. E. Li, H. Ma, B. Cheng, T. H. Lee, “Policy Iteration Based Approximate Dynamic Programming Toward Autonomous Driving in Constrained Dynamic Environment,” IEEE Transactions on Intelligent Transportation Systems, pp. 1–11, 2023.
13. Z. Lin*, J. Duan*, S. E. Li, H. Ma, J. Li, J. Chen, B. Cheng, J. Ma, “Policy-Iteration-Based Finite-Horizon Approximate Dynamic Programming for Continuous-Time Nonlinear Optimal Control,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1–13, Jan. 2022.
14. Z. Gu, Y. Yin, S. E. Li, J. Duan, F. Zhang, S. Zheng, R. Yang, “Integrated eco-driving automation of intelligent vehicles in multi-lane scenario via model-accelerated reinforcement learning,” Transportation Research Part C, vol. 144, 103863, 2022.
15. Y. Ren, J. Jiang, G. Zhan, S. E. Li, C. Chen, K. Li, J. Duan, “Self-Learned Intelligence for Integrated Decision and Control of Automated Vehicles at Signalized Intersections,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 24145–24156, Nov. 2021.    Download
16. Y. Guan, Y. Ren, Q. Sun, S. E. Li, H. Ma, J. Duan, Y. Dai, B. Cheng, “Integrated Decision and Control: Toward Interpretable and Computationally Efficient Driving Intelligence,” IEEE Transactions on Cybernetics, pp. 1–15, 2022.    Download
17. B. Peng, J. Duan et al., “Model-Based Chance-Constrained Reinforcement Learning via Separated Proportional-Integral Lagrangian,” pp. 1–13, Jan. 2022.    Download
18. Z. Liu*, J. Duan*, W. Wang, S. E. Li, Y. Yin, Z. Lin, B. Cheng, “Recurrent Model Predictive Control: Learning an Explicit Recurrent Controller for Nonlinear Systems,” vol. 69, no. 10, pp. 10437–10446, Oct. 2022.    Download
19. J. Duan, Z. Liu, Shengbo Eben Li, F. B. Hu, Z. Jia, and B. Cheng, “Adaptive dynamic programming for nonaffine nonlinear optimal control problem with state constraints,” vol. 484, pp. 128–141, May 2022.‌    Download
20. J. Duan et al., “Fixed-Dimensional and Permutation Invariant State Representation of Autonomous Driving,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 9518–9528, Jul. 2022.‌    Download
21. J. Duan, Y. Guan, S. E. Li, Y. Ren, Q. Sun, and B. Cheng, “Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1–15, 2021.‌    Download
22. Y. Guan, S. E. Li, J. Duan, J. Li, Y. Ren, Q. Sun, B. Cheng, “Direct and indirect reinforcement learning,” International Journal of Intelligent Systems, vol. 36, no. 8, pp. 4439–4467, May 2021.    Download
23. J. Duan, S. Li, Y. Guan, Q. Sun, and B. Cheng, “Hierarchical Reinforcement Learning for Self-Driving Decision-Making without Reliance on Labeled Driving Data,” IET Intelligent Transport Systems, Jan. 2020.‌    Download
24. L. Hou*, J. Duan*, W. Wang, R. Li, G. Li, B. Cheng, “Drivers’ Braking Behaviors in Different Motion Patterns of Vehicle-Bicycle Conflicts,” vol. 2019, pp. 1–17, Mar. 2019.
25. 李升波, 关阳, 侯廉, 高洪波, 段京良, 梁爽, 汪玉, 成波, 李克强, 任伟，李骏. “深度神经网络的关键技术及其在自动驾驶领域的应用,” 汽车安全与节能学报, vol. 10, no. 2, pp. 119-145, 2019.
26. Y. Guan, S. E. Li, J. Duan, W. Wang, B. Cheng, “Markov probabilistic decision making of self-driving cars in highway with random traffic flow: a simulation study,” Journal of Intelligent and Connected Vehicles, vol. 1, no. 2, pp. 77-84, 2018.
27. J. Duan, R. Li, L. Hou, W. Wang, G. Li, S. E. Li, B. Cheng, H. Gao, “Driver braking behavior analysis to improve autonomous emergency braking systems in typical Chinese vehicle-bicycle conflicts,”Accident Analysis & Prevention, vol. 108, pp. 74–82, Nov. 2017.
28. S. E. Li, Q. Guo, S. Xu, J. Duan, S. Li, C. Li, K. Su, “Performance enhanced predictive control for adaptive cruise control system considering road elevation information,” IEEE Transactions on Intelligent Vehicles, vol. 2, no. 3, pp. 150-160, 2017.

Conference Papers

1. H. Yan, H. Xu, H. Gao, F. Ma, S. E. Li, J. Duan*, “Integrated Drill Boom Hole-Seeking Control via Reinforcement Learning” 2023 IEEE International Conference on Unmanned System (ICUS), Hefei, China, 2023.
2. X. Song, J. Duan, W. Wang, S. E. Li, C. Chen, B. Cheng, B. Zhang, J. Wei, X. S. Wang, “LipsNet: A Smooth and Robust Neural Network with Adaptive Lipschitz Constant for High Accuracy Optimal Control,” International Conference on Machine Learning (ICML), Hawaii, USA, 2023.
3. G. Zhan, Y. Jiang, J. Duan, S. E. Li, B. Cheng, K. Li, “Continuous-Time Policy Optimization,” 2023 American Control Conference (ACC), San Diego, CA, USA, 2023.
4. X. Chen, J. Duan, Y. Liang, L. Zhao, “Global Convergence of Two-timescale Actor-Critic for Solving Linear Quadratic Regulator,” Association for the Advancement of Artificial Intelligence (AAAI), San Antonio, TX, USA, 2023.    Download
5. Q. Ge, G. Sartoretti, J. Duan, S. E. Li, Y. Yin, S. Zheng, “Distributed Model Predictive Control of Connected Multi-Vehicle Systems at Unsignalized Intersections,” 2022 IEEE International Conference on Unmanned Systems (ICUS), Guangzhou, China, 2022.
6. J. Duan, W. Cao, Y. Zheng, L. Zhao, “On the Optimization Landscape of Dynamic Output Feedback: A Case Study for Linear Quadratic Regulator,” 2022 IEEE International Conference on Decision and Control (CDC), Cancún, Mexico, 2022.    Download
7. W. Cao, J. Duan, S. E. Li, C. Chen, C. Liu, Y. Wang, “Primal-Dual Estimator Learning Method with Feasibility and Near-Optimality Guarantees,” 2022 IEEE International Conference on Decision and Control (CDC), Cancún, Mexico, 2022.    Download
8. J. Duan, J. Li, Z. Lin, “Optimization Landscape of Gradient Descent for Discrete-time Static Output Feedback,” 2022 American Control Conference (ACC), Atlanta, Georgia, USA, 2022.    Download
9. J. Duan, F. Zhang, S. E. Li, Y. Ren, B. Cheng, Z. Xin, “Applications of Distributional Soft Actor-Critic in Real-world Autonomous Driving,” 2022 IEEE International Conference on Computer, Control and Robotics (ICCCR), Shanghai, China, 2022.
10. W. Cao, J. Chen, J. Duan, S. E. Li, Y. Lyu, Z. Gu, Y. Zhang, “Reinforced Optimal Estimator,” 2021 Modeling, Estimation and Control Conference (MECC), Austin, Texas, USA, 2021, pp. 366-373.    Download
11. Z. Gu, Y. Yang, J. Duan, S. E. Li, J. Chen, W. Cao, S. Zheng, “Belief State Separated Reinforcement Learning for Autonomous Vehicle Decision Making under Uncertainty,” 2021 IEEE International Conference on Intelligent Transportation Systems (ITSC), Indianapolis, IN, USA, 2021, pp. 586-592.    Download
12. B. Peng, Y. Mu, J. Duan, Y. Guan, S. E. Li, J. Chen, “Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning,” 2021 IEEE Intelligent Vehicle Symposium (IV), Nagoya University, Nagoya, Japan, 2021. (Best Student Paper Award finalist)    Download
13. Z. Lin*, J. Duan*, S. E. Li, J. Li, H. Ma, Q. Sun, J. Chen, B. Cheng, “Solving Finite-horizon HJB for Optimal Control of Continuous-time Systems,” 2021 IEEE International Conference on Computer, Control and Robotics (ICCCR), Shanghai, Beijing, 2021. (* equal contributors)
14. Y. Ren*, J. Duan*, S. E. Li, Y. Guan, Q. Sun, “Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-critic,” 2020 IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, 2020, pp. 1-6. (* equal contributors, Best Student Paper Award)    Download
15. L. Wen*, J. Duan*, S. E. Li, S. Xu, H. Peng, “Safe reinforcement learning for autonomous vehicles through parallel constrained policy optimization,” 2020 IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, 2020. (* equal contributors)    Download
16. Z. Lin*, J. Duan*, S. E. Li, H. Ma, Y. Yin, B. Cheng, “Continuous-time Finite-horizon ADP for Automated Vehicle Controller Design with High Efficiency,” 2020 IEEE International Conference on Unmanned Systems (ICUS), Harbin, China, 2020, 978-984. (* equal contributors, Best Paper Award)    Download
17. J. Duan, S. E. Li, B. Cheng, Y. Guan, Q. Sun, B. Cheng, “Hierarchical Reinforcement Learning for Decision Making of Self-Driving Cars without Reliance on Labeled Driving Data.,” 14th International Symposium on Advanced Vehicle Control, AVEC'18, Beijing, China, July 16-20, 2018, pp. 1-7. (Best Paper Award finalist)    Download

Book Chapter

1. S. E. Li, L. Xin, C. Liu, J. Duan, and S. E. Li, “Promoting connected and automated vehicles with cooperative sensing and control technology,” pp. 515–531, Sep. 2019, doi: https://doi.org/10.1049/pbtr025e_ch23. Chapter 23 in book: Cooperative Intelligent Transport Systems: Towards high-level automated driving, pp. 515-528, 2019, IET.
2. J. Chen, J. Duan, Y. Guan, Q. Sun, Y. Yin, and S. E. Li, “Self-learning Decision and Control for Highly Automated Vehicles,” Chapter 10 in book: AI-enabled Technologies for Autonomous and Connected Vehicles, pp. 307–330, Sep. 2022, doi: https://doi.org/10.1007/978-3-031-06780-8_11. ‌    Download

ArXiv Papers