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意大利自行车闯红灯行为:一项观察性研究。

Red-light running behavior of cyclists in Italy: An observational study.

机构信息

Department of Psychology, Alma Mater Studiorum, University of Bologna, Via Berti Pichat 5, 40126, Bologna, Italy.

Department of Psychology, Alma Mater Studiorum, University of Bologna, Via Berti Pichat 5, 40126, Bologna, Italy.

出版信息

Accid Anal Prev. 2018 Nov;120:219-232. doi: 10.1016/j.aap.2018.08.013. Epub 2018 Aug 29.

DOI:10.1016/j.aap.2018.08.013
PMID:30172107
Abstract

Accident analysis and studies on traffic revealed that cyclists' violation of red-light regulation is a typical infringement committed by cyclists. Furthermore, an association between cyclists' crash involvement and red-light violations has been found across different countries. The literature on red-light running cyclists' behavior in relation to their characteristic is still scarce. The present study, adopted an eye-observational methodology to investigates differences in cyclists' crossing behavior at intersections, with a particular attention to their demographical characteristics. The classification of cyclists' red-light behavior in risk-taking, opportunistic and law-obeying, was adopted and re-adapted to reflect more objective behaviors, eliminating any inference or judgment. Two researchers at a time observed unobtrusively at four different intersections, during morning and late afternoon peak hours, 1381 cyclists approaching the traffic light during the red phase. More than 60% of the observed cyclists violated the traffic control. Results showed that the visual search strategy displayed by the cyclists and the presence of other cyclists at the intersection are important factors in predicting the probability of red-light running behavior.

摘要

事故分析和交通研究表明,自行车闯红灯是自行车手典型的违法行为。此外,不同国家都发现自行车事故的发生与闯红灯之间存在关联。关于闯红灯的自行车手行为及其特征的文献仍然很少。本研究采用眼动观测方法,特别关注其人口统计学特征,研究了自行车手在交叉口的穿越行为差异。本研究采用并重新调整了将自行车手的闯红灯行为分为冒险、机会主义和守法三种分类方法,以反映更客观的行为,避免任何推断或判断。两名研究人员在四个不同的交叉口进行了非干扰式观察,在早晚高峰时段,有 1381 名自行车手在红灯期间接近交通灯。超过 60%的观察到的自行车手违反了交通管制。结果表明,自行车手的视觉搜索策略和交叉口其他自行车手的存在是预测闯红灯行为概率的重要因素。

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