Department of Civil Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L7, Canada.
Accid Anal Prev. 2021 Sep;159:106283. doi: 10.1016/j.aap.2021.106283. Epub 2021 Jul 3.
The main goal of this study is to investigate the impact of a variety of factors on the frequency and the severity of pedestrian-vehicle collisions that involve pedestrian violations. To that end, the collision dataset of the City of Hamilton between 2010 and 2017 was reviewed to filter out pedestrian collisions that involved pedestrian violations. A Latent Class Analysis (LCA) method was applied to divide the dataset into a set of homogeneous clusters, based on traffic and intersection characteristics. A copula-based multivariate model was then developed for each cluster in order to study the impact of the different factors on collisions under the prevailing conditions of each cluster. The results showed that the number of bus stops within the intersection area is directly associated with the frequency and the severity of collisions involving pedestrian violations. A reduction in collisions was observed with the increase in the frequency of buses at intersections that are located along main transit routes. Moreover, the presence of schools near the intersection tends to increase the frequency of collisions involving pedestrian violations, especially at large intersections. The results also revealed that the presence of central refuge islands, despite their overall safety benefits, increases the likelihood of collisions involving pedestrian violations in large intersections. The results of this study provide valuable insights for a better understanding of the safety consequences of pedestrian violations. Such understanding assists engineers and planners to design intersections that reduce the frequency of pedestrian violations and mitigate their negative safety consequences.
本研究的主要目的是探讨各种因素对涉及行人违规的行人和车辆碰撞的频率和严重程度的影响。为此，回顾了 2010 年至 2017 年汉密尔顿市的碰撞数据集，以筛选出涉及行人违规的行人碰撞。然后，应用潜在类别分析（LCA）方法根据交通和交叉口特征将数据集划分为一组同质聚类。然后为每个聚类开发了基于 Copula 的多元模型，以便在每个聚类的现有条件下研究不同因素对碰撞的影响。结果表明，交叉口区域内的公共汽车站数量与涉及行人违规的碰撞的频率和严重程度直接相关。随着位于主要交通路线上的交叉口处公交车的频率增加，观察到碰撞减少。此外，交叉口附近有学校会增加涉及行人违规的碰撞的频率，尤其是在大型交叉口。结果还表明，中央安全岛的存在尽管有整体安全效益，但会增加大型交叉口涉及行人违规的碰撞的可能性。本研究的结果为更好地理解行人违规的安全后果提供了有价值的见解。这种理解有助于工程师和规划人员设计减少行人违规频率并减轻其负面安全后果的交叉口。
