基于stackelberg博弈的考虑驾驶员神经肌肉延迟特性的驾驶自动化共享转向控制

Jun Liu , Hongyan Guo , Wanqing Shi , Qikun Dai , Jiaming Zhang
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引用次数: 2

摘要

为了提高智能车辆的安全性,减少驾驶员转向工作量,采用stackelberg博弈论设计了考虑驾驶员神经肌肉延迟特性的共享转向控制策略。首先,提出了一种可调节驾驶权的共享转向控制框架,并利用stackelberg博弈论建立了考虑驾驶员神经肌肉延迟特性的耦合交互模型。在此基础上,从理论上推导了达到博弈均衡时的驾驶员-自动化最优控制策略。最后,通过仿真和虚拟驾驶试验验证了所提方法的优越性。结果表明,该方法可以在低驾驶重量干预的情况下提高车辆的安全性,并能以较低的控制成本获得较好的辅助效果。此外,驾驶员在环测试结果表明,该策略可以更好地辅助低驾驶技能的驾驶员。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Driver-automation shared steering control considering driver neuromuscular delay characteristics based on stackelberg game

Driver-automation shared steering control considering driver neuromuscular delay characteristics based on stackelberg game

To promote the intelligent vehicle safety and reduce the driver steering workload, stackelberg game theory is adopted to design the shared steering control strategy that takes the driver neuromuscular delay characteristics into account. First, a shared steering control framework with adjustable driving weight is proposed, and a coupling interaction model considering the driver neuromuscular delay characteristics is constructed by using the stackelberg game theory. Moreover, the driver-automation optimal control strategy is deduced theoretically when the game equilibrium is reached. Finally, simulation and virtual driving tests are carried out to verify the superiority of the proposed method. The results illustrate that the raised method can enhance the vehicle safety with low driving weight intervention, and it can achieve better auxiliary effect with less control cost. In addition, the driver-in-the-loop test results show that the proposed strategy can achieve better performance in assisting drivers with low driving skills.

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