Driver support systems that include human states in the support process is an active research field. Many recent approaches allow, for example, to sense the driver's drowsiness or awareness of the driving situation. However, so far, this rich information has not been utilized much for improving the effectiveness of support systems. In this paper, we therefore propose a warning system that uses human states in the form of driver errors and can warn users in some cases of upcoming risks several seconds earlier than the state of the art systems not considering human factors. The system consists of a behavior planner Risk Maps which directly changes its prediction of the surrounding driving situation based on the sensed driver errors. By checking if this driver's behavior plan is objectively safe, a more robust and foresighted driver warning is achieved. In different simulations of a dynamic lane change and intersection scenarios, we show how the driver's behavior plan can become unsafe, given the estimate of driver errors, and experimentally validate the advantages of considering human factors.

翻译：将人类状态纳入支持过程的驾驶员辅助系统是一个活跃的研究领域。许多近期方法例如能够感知驾驶员的困倦程度或对驾驶情境的察觉能力。然而，迄今为止，这些丰富信息尚未被充分利用以提高支持系统的有效性。为此，本文提出了一种预警系统，该系统以驾驶员错误的形式利用人类状态，能够在某些情况下比未考虑人为因素的现有系统提前数秒警告用户即将发生的风险。该系统由一个行为规划器"风险图"构成，该规划器基于检测到的驾驶员错误直接改变其对周围驾驶情境的预测。通过检查该驾驶员行为规划是否客观安全，可实现更鲁棒且更具前瞻性的驾驶员预警。在动态车道变换和交叉路口场景的不同仿真中，我们展示了在给定驾驶员错误估计的情况下，驾驶员行为规划如何可能变得不安全，并通过实验验证了考虑人为因素的优势。