Department of Civil & Environmental Engineering, Florida International University, 10555, West Flagler, United States.
School of Engineering, University of North Florida, 1 UNF Drive, Jacksonville, FL, 32224, United States.
Accid Anal Prev. 2019 Jan;122:215-225. doi: 10.1016/j.aap.2018.10.008. Epub 2018 Oct 31.
Many campaigns promote walking for recreation, work, and general-purpose trips for health and environmental benefits. This study investigated factors that influence the occurrence of crashes involving elderly pedestrians in relation to where they reside. Using actual pedestrian residential addresses, a Google integrated GIS-based method was developed for estimating distances from crash locations to pedestrian residences. A generalized linear mixed model (GLMM) was used to evaluate the effect of factors associated with residences, such as age group, roadway features, and demographic characteristics on the proximity of crash locations. Results indicated that the proximity of crash locations to pedestrian residences is influenced by the pedestrian age, gender, roadway traffic volume, seasons of the year, and pedestrian residence demographic characteristics. The findings of this study can be used by transportation agencies to develop plans that enhance aging pedestrian safety and improve livability.
许多活动都提倡步行娱乐、工作和一般用途的出行,以获得健康和环境效益。本研究调查了影响与老年人行人相关的事故发生的因素,这些事故与他们的居住地有关。使用实际的行人居住地址,开发了一种基于 Google 集成 GIS 的方法,用于估算事故地点与行人住所之间的距离。使用广义线性混合模型 (GLMM) 来评估与住所相关的因素(如年龄组、道路特征和人口特征)对事故地点接近程度的影响。结果表明,事故地点与行人住所的接近程度受到行人年龄、性别、道路交通量、季节和行人住所人口特征的影响。本研究的结果可被交通机构用于制定计划,以提高老年行人的安全性并提高宜居性。