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A Unifying Theory of Driver Perception and Steering Control on Straight and Winding Roads

机译:直线和绕组道路司机感知和转向控制的统一理论

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摘要

Novel driver support systems potentially enhance road safety by cooperating with the human driver. To optimize the design of emerging steering support systems, a profound understanding of driver steering behavior is required. This article proposes a new theory of driver steering, which unifies visual perception and control models. The theory is derived directly from measured steering data, without any a priori assumptions on driver inputs or control dynamics. Results of a human-in-the-loop simulator experiment are presented, in which drivers tracked the centerline of straight and winding roads. Multiloop frequency response function (FRF) estimates reveal how drivers use visual preview, lateral position feedback, and heading feedback for control. Classical control theory is used to model all three FRF estimates. The model has physically interpretable parameters, which indicate that drivers minimize the bearing angle to an "aim point" (located 0.25-0.75 s ahead) through simple compensatory control, both on straight and winding roads. The resulting unifying perception and control theory provides a new tool for rationalizing driver steering behavior, and for optimizing modern steering support systems.
机译:新颖的驾驶员支持系统可能通过与人类司机合作来提高道路安全性。为了优化新出现的转向支持系统的设计,需要对驾驶员转向行为的深刻理解。本文提出了一种新的司机转向理论,统一了视觉感知和控制模型。该理论直接从测量的转向数据导出,而无需对驾驶员输入或控制动态的任何先验假设。介绍了LOOP模拟器实验的结果,其中司机跟踪了直线和绕线道路的中心线。 MultiLoop频率响应函数(FRF)估计揭示了驱动程序如何使用视觉预览,横向位置反馈和用于控制的前置反馈。古典控制理论用于模拟所有三个FRF估计。该模型具有物理可解释的参数,这表明驾驶员通过简单的补偿控制在直线和蜿蜒的道路上通过简单的补偿控制将轴承角度最小化到“瞄准点”(前进0.25-0.75)。由此产生的统一感知和控制理论提供了一种用于合理化驱动器转向行为的新工具,以及优化现代转向支持系统。

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