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参与实验室科研项目
人机混合智能系统双层智能测试评估技术研究
复杂环境下非完全信息博弈决策的智能基础模型研究
学术成果
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Conference Articles
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A Shared Control Strategy Considering Control Fusion Security for Human-Machine Co-Driving System
Xiaojun Zhu,
Bin Lan,
Wen Zhang,
Yun-Bo Zhao ,
Yu Kang,
and Binkun Liu
In The 44th Chinese Control Conference (CCC 2025)
2025
[Abs]
[pdf]
In human- machine cooperative control, it should be ensured that the system is safe and stable as well as efficient in accomplishing the task. Especially in safety critical systems, such as human-machine co-driving systems, ensuring safety is the first priority and other performances may need to be sacrificed to ensure safety. In this case, it is difficult to guarantee other performances of the human-machine co-driving system (e.g., tracking performance). Existing shared control methods cannot guarantee good tracking performance while keeping the system safe. To address this problem, this paper proposes a shared control strategy that takes security into account to ensure system security and stability while realizing good trajectory tracking performance. The effectiveness of the proposed strategy is verified in experiments. The results show that the proposed shared control strategy reduces the trajectory tracking error while ensuring safety.