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Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model

机译:基于模糊元胞自动机(FCA)模型的信号交叉口右转过滤运动驾驶员认知失误和驾驶错误的安全性评估

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摘要

This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance.
机译:本文提出了一种基于仿真的方法来估计驾驶员认知故障和驾驶错误的安全影响。涉及语言术语和不确定性的模糊逻辑与元胞自动机模型相结合,以模拟信号交叉口右转过滤运动的决策过程。进行模拟实验以估计认知故障与驾驶错误之间的关系以及安全性能。仿真结果表明,发现不同类型的认知障碍与驾驶错误和安全性能有着不同的关系。对于右转过滤运动,认知故障更有可能导致驾驶错误,而交通流的冲突则更加密集。此外,发现不同的驾驶错误具有不同的安全影响。这项研究提供了一种新颖的方法,可以在语言上评估认知并复制单个驾驶员的决策程序。与碰撞分析相比,提出的FCA模型可以定量估计特定的认知故障,以及认知对驾驶错误和安全性能的影响。

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