An analysis of the injury severity of pedestrians in Brazil using random parameters logit models

Mateus Nogueira Silva, Flávio José Craveiro Cunto, Marcos José Timbó Lima Gomes, Sara Ferreira
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Abstract

In Brazil, pedestrians represent the third largest group of crash victims, after motorcyclists and car occupants. Implementing measures to ensure pedestrian safety and prioritization requires an understanding of the risk factors associated with crash injuries. In this study, a random-parameter logit model was estimated to investigate factors influencing the severity of crashes with pedestrians in urban roads in Fortaleza, Brazil. A sample of 2,660 observations of crashes with pedestrians in the city from 2017 to 2019 was used. The injury severity levels adopted by the Crash Information System (SIAT) were grouped into three categories: mild/moderate, severe and fatal. From the investigated factors, only the variable related to the pedestrian's age over 60 years old obtained a significant random parameter. In this case, the heterogeneity in the observations may be associated, among other factors, to the body’s physical fragility and the cognitive function that may differ among individuals in this group. The results showed that the driver’s gender and age, the crash site, the motorcycle use, and the presence of speed cameras did not have a significant impact on the severity of crashes with pedestrians. On the other hand, crashes occurring at night, with heavy vehicles, on weekends, and located on roads with higher traffic classification are associated with more severe injuries. The incorporation of unobserved heterogeneity in the estimation of the model's parameters stands out as one of the main contributions of this work.
巴西行人伤害严重程度的随机参数logit模型分析
在巴西,行人是车祸受害者的第三大群体,仅次于摩托车手和汽车乘客。实施确保行人安全和优先次序的措施需要了解与碰撞伤害相关的风险因素。在这项研究中,估计了一个随机参数的logit模型,以调查在巴西福塔莱萨城市道路上行人碰撞严重程度的影响因素。该研究使用了2017年至2019年期间该市2660起行人撞车事故的观察样本。碰撞信息系统(SIAT)采用的伤害严重程度分为三类:轻度/中度,严重和致命。在所调查的因素中,只有与行人年龄大于60岁相关的变量获得了显著的随机参数。在这种情况下,除了其他因素外,观察结果的异质性可能与身体的脆弱性和认知功能有关,这些因素在该组个体之间可能存在差异。结果表明,驾驶员的性别和年龄、碰撞地点、摩托车使用情况和测速摄像头的存在对行人碰撞的严重程度没有显著影响。另一方面,发生在夜间、重型车辆、周末以及交通等级较高的道路上的撞车事故与更严重的伤害有关。在模型参数估计中纳入未观察到的异质性是这项工作的主要贡献之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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