Fangjian Li

Ph.D. from Clemson University

I received my Ph.D. degree in Mechanical Engineering Department at Clemson University (May 2022), and my master’s degree in Automotive Engineering at Clemson. My research focuses on the human-aware autonomous driving algorithms, i.e., how the presence of human drivers can affect or help the autonomous driving systems. The techniques involved in my research are (inverse) reinforcement learning, imitation learning, optimal control, and Bayesian inference. I am currently an engineer specializing in prediction and behavior planning for autonomous driving systems.

selected publications

  1. ACC
    Adversarial Learning for Safe Highway Driving based on Two-Player Zero-Sum Game
    Li, Fangjian, Zhao, Mengtao, Wagner, John, and Wang, Yue
    2023 American Control Conference (ACC) 2023
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  2. ASME J-AVS
    Safety-aware Adversarial Inverse Reinforcement Learning (S-AIRL) for Highway Autonomous Driving
    Li, Fangjian, Wagner, John R, and Wang, Yue
    ASME Journal of Autonomous Vehicles and Systems 2022
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  3. IEEE T-ITS
    Unmanned Ground Vehicle Platooning under CyberAttacks: A Human-Robot Interaction Framework
    Li, Fangjian, Wang, Chengshi, Mikulski, Dariusz, Wagner, John R, and Wang, Yue
    IEEE Transactions on Intelligent Transportation Systems 2022
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  4. IEEE T-ITS
    Cooperative adaptive cruise control for string stable mixed traffic: Benchmark and human-centered design
    Li, Fangjian, and Wang, Yue
    IEEE Transactions on Intelligent Transportation Systems 2017
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  5. IEEE T-ITS
    A review of sensing and communication, human factors, and controller aspects for information-aware connected and automated vehicles
    Sarker, Ankur, Shen, Haiying, Rahman, Mizanur, Chowdhury, Mashrur, Dey, Kakan, Li, Fangjian, Wang, Yue, and Narman, Husnu S
    IEEE Transactions on Intelligent Transportation Systems 2019
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