Chai Chen, Wong Yiik Diew, Wang Xuesong
The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai, 201804, China; College of Transportation Engineering, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Centre for Infrastructure Systems, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore.
Accid Anal Prev. 2017 Jul;104:156-164. doi: 10.1016/j.aap.2017.04.026. Epub 2017 May 19.
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.
本文提出了一种基于模拟的方法来估计驾驶员认知失误和驾驶错误对安全的影响。模糊逻辑涉及语言术语和不确定性,它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失误和驾驶错误与安全性能之间的关系。模拟结果表明,不同类型的认知失误与驾驶错误和安全性能之间存在不同的关系。对于右转过滤运动,在交通流冲突更密集的情况下,认知失误更有可能导致驾驶错误。此外,发现不同的驾驶错误具有不同的安全影响。该研究旨在提供一种新颖的方法,从语言角度评估认知,并复制个体驾驶员的决策程序。与碰撞分析相比,所提出的FCA模型允许对特定的认知失误以及认知对驾驶错误和安全性能的影响进行定量估计。