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<p>To mitigate human–machine conflicts arising from divergent control objectives in collaborative steering, this paper presents a novel steering strategy grounded in Stackelberg game theory. Leveraging the Stackelberg framework, an adaptive authority adjustment mechanism is introduced, which dynamically adjusts based on a driver aggression coefficient and an elliptical risk metric. The proposed approach’s effectiveness is validated through hardware-in-the-loop experimentation. Experimental results confirm that both the collaborative steering and authority adjustment strategies, driven by Stackelberg game theory, effectively minimize conflicts caused by mismatched control intentions. This approach enhances vehicle safety, preserves driver autonomy to a degree, and adapts assistance levels to accommodate varying driver behaviors.</p>

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Personalized Human–Machine Steering Control Strategy Using Stackelberg Game and Authority Flexibility

  • 期刊论文

  • 发表日期：

    2025年7月26日

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  • Zhengang Gao,
  • Pengzhou Li,
  • Ning Wang,
  • Dequan Pu

摘要

To mitigate human–machine conflicts arising from divergent control objectives in collaborative steering, this paper presents a novel steering strategy grounded in Stackelberg game theory. Leveraging the Stackelberg framework, an adaptive authority adjustment mechanism is introduced, which dynamically adjusts based on a driver aggression coefficient and an elliptical risk metric. The proposed approach’s effectiveness is validated through hardware-in-the-loop experimentation. Experimental results confirm that both the collaborative steering and authority adjustment strategies, driven by Stackelberg game theory, effectively minimize conflicts caused by mismatched control intentions. This approach enhances vehicle safety, preserves driver autonomy to a degree, and adapts assistance levels to accommodate varying driver behaviors.