Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.
Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.
J Safety Res. 2020 Jun;73:119-132. doi: 10.1016/j.jsr.2020.02.020. Epub 2020 Mar 10.
A pedestrian crash occurs due to a series of contributing factors taking effect in an antecedent-consequent order. One specific type of antecedent-consequent order is called a crash causation pattern. Understanding crash causation patterns is important for clarifying the complicated growth of a pedestrian crash, which ultimately helps recommend corresponding countermeasures. However, previous studies lack an in-depth investigation of pedestrian crash cases, and are insufficient to propose a representative picture of causation patterns.
In this study, pedestrian crash causation patterns were discerned by using the Driving Reliability and Error Analysis Method (DREAM). One hundred and forty-two pedestrian crashes were investigated, and five pedestrian pre-crash scenarios were extracted. Then, the crash causation patterns in each pre-crash scenario were analyzed; and finally, six distinct patterns were identified. Accordingly, 17 typical situations corresponding to these causation patterns were specified as well.
Among these patterns, the pattern related to distracted driving and the pattern related to an unexpected change of pedestrian trajectory contributed to a large portion of the total crashes (i.e., 27% and 24%, respectively). Other patterns also played an important role in inducing a pedestrian crash; these patterns include the pattern related to an obstructed line of sight caused by outside objects (9%), the pattern that involves reduced visibility (13%), and the pattern related to an improper estimation of the gap distance between the vehicle and the pedestrian (10%). The results further demonstrated the inter-heterogeneity of a crash causation pattern, as well as the intra-heterogeneity of pattern features between different pedestrian pre-crash scenarios. Conclusions and practical applications: Essentially, a crash causation pattern might involve different contributing factors by nature or dependent on specific scenarios. Finally, this study proposed suggestions for roadway facility design, roadway safety education and pedestrian crash prevention system development.
行人事故是由于一系列相继发生的因素共同作用的结果。有一种特定的相继顺序称为事故致因模式。理解事故致因模式对于阐明行人事故的复杂发展过程非常重要，这有助于提出相应的对策。然而，以前的研究缺乏对行人事故案例的深入调查，不足以提出有代表性的致因模式图。
本研究采用驾驶可靠性和误差分析方法（DREAM）来识别行人事故致因模式。调查了 142 起行人事故，提取了 5 个行人事故前场景。然后，分析了每个事故前场景中的事故致因模式，最终确定了 6 种不同的模式。相应地，还确定了 17 种与这些致因模式相对应的典型情况。
在这些模式中，与分心驾驶相关的模式和与行人轨迹意外变化相关的模式导致了大部分事故（分别为 27%和 24%）。其他模式也在导致行人事故方面发挥了重要作用；这些模式包括由外部物体引起的视线受阻模式（9%）、能见度降低模式（13%）和车辆与行人之间的间隙距离估计不当模式（10%）。结果进一步表明了事故致因模式的异质性，以及不同行人事故前场景中模式特征的同质性。结论和实际应用：本质上，一个事故致因模式可能涉及不同的因素，或者取决于特定的场景。最后，本研究提出了关于道路设施设计、道路安全教育和行人事故预防系统发展的建议。
