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.

中文翻译：

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直线和弯曲道路上驾驶员感知和转向控制的统一理论

新型驾驶员支持系统通过与人类驾驶员合作，有可能提高道路安全。为了优化新兴转向支持系统的设计，需要深入了解驾驶员的转向行为。本文提出了一种新的驾驶员转向理论，它统一了视觉感知和控制模型。该理论直接来自测量的转向数据，没有对驾驶员输入或控制动态进行任何先验假设。展示了人在回路模拟器实验的结果，其中驾驶员跟踪笔直和蜿蜒道路的中心线。多回路频率响应函数 (FRF) 估计揭示了驾驶员如何使用视觉预览、横向位置反馈和航向反馈进行控制。经典控制理论用于对所有三个 FRF 估计进行建模。该模型具有物理上可解释的参数，这表明驾驶员通过简单的补偿控制将方位角最小化到“目标点”（位于前方 0.25-0.75 秒），无论是在笔直道路还是蜿蜒道路上。由此产生的统一感知和控制理论为合理化驾驶员转向行为和优化现代转向支持系统提供了一种新工具。