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Investigating the gender differences on bicycle-vehicle conflicts at urban intersections using an ordered logit methodology

机译:使用有序logit方法研究城市交叉口的自行车与机动车冲突的性别差异

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摘要

In the literature, a crash-based modeling approach has long been used to evaluate the factors that contribute to cyclist injury risk at intersections. However, this approach has been criticized as crashes are required to occur before contributing factors can be identified and countermeasures can be implemented. Moreover, human factors related to dangerous behaviors are difficult to evaluate using crash-based methods. As an alternative, surrogate safety measures have been developed to address the issue of reliance on crash data. Despite recent developments, few methodologies and little empirical evidence exist on bicycle-vehicle interactions at intersections using video-based data and statistical analyses to identify associated factors. This study investigates bicycle-vehicle conflict severity and evaluates the impact of different factors, including gender, on cyclist risk at urban intersections with cycle tracks. A segmented ordered logit model is used to evaluate post-encroachment time between cyclists and vehicles. Video data was collected at seven intersections in Montreal, Canada. Road user trajectories were automatically extracted, classified, and filtered using a computer vision software to yield 1514 interactions. The discrete choice variable was generated by dividing post-encroachment time into normal interactions, conflicts, and dangerous conflicts. Independent variables reflecting attributes of the cyclist, vehicle, and environment were extracted either automatically or manually. Results indicated that an ordered model is appropriate for analyzing traffic conflicts and identifying key factors. Furthermore, exogenous segmentation was beneficial in comparing different segments of the population within a single model. Male cyclists, with all else being equal, were less likely than female cyclists to be involved in conflicts and dangerous conflicts at the studied intersections. Bicycle and vehicle speed, along with the time of the conflict relative to the red light phase, were other significant factors in conflict severity. These results will contribute to and further the understanding of gender differences in cycling within North America. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在文献中,基于碰撞的建模方法长期以来一直用于评估导致交叉路口骑车者受伤风险的因素。但是,这种方法已受到批评,因为必须先发生崩溃,才能识别出影响因素并采取对策。而且,与危险行为有关的人为因素很难使用基于碰撞的方法进行评估。作为替代方案,已经开发了替代安全措施来解决依赖碰撞数据的问题。尽管有最近的发展,但是在交叉路口使用基于视频的数据和统计分析来识别相关因素时,关于自行车与汽车的相互作用的方法学和经验证据很少。这项研究调查了自行车与机动车之间的冲突严重程度,并评估了包括性别在内的不同因素对具有自行车道的城市交叉路口骑自行车者的风险的影响。分段有序logit模型用于评估骑自行车者和车辆之间的侵犯后时间。视频数据是在加拿大蒙特利尔的七个十字路口收集的。使用计算机视觉软件自动提取,分类和过滤道路用户的轨迹,以产生1514个交互。离散选择变量是通过将入侵后的时间划分为正常互动,冲突和危险冲突而生成的。自动或手动提取反映自行车手,车辆和环境属性的自变量。结果表明,有序模型适用于分析交通冲突和识别关键因素。此外,外源分割对于在单个模型中比较人口的不同部分是有益的。在其他条件相同的情况下,男性骑自行车的人比女性骑自行车的人在所研究的交叉口处发生冲突和危险冲突的可能性较小。自行车和车辆的速度,以及与红灯相相关的冲突时间,是造成冲突严重程度的其他重要因素。这些结果将有助于并进一步了解北美地区自行车运动中的性别差异。 (C)2016 Elsevier Ltd.保留所有权利。

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