Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
Accid Anal Prev. 2019 Jul;128:17-24. doi: 10.1016/j.aap.2019.03.017. Epub 2019 Apr 4.
Pedestrian are vulnerable to severe injury and mortality in the road crashes. Understanding the essence of the pedestrian crash is important to the development of effective safety countermeasures and improvement of social well-being. It is necessary to measure the exposure for the quantification of pedestrian crash risk. The primary goals of this study are to explore the efficient exposure measure for pedestrian crash, and identify the possible factors contributing to the incidence of pedestrian crash. In this study, amount of travel was estimated based on the Travel Characteristic Survey (TCS) data in 2011, and the crash data were obtained from the Transport Information System (TIS) of the Hong Kong Transport Department during the period from 2011 to 2015. Total population, walking frequency and walking time were adopted to represent the pedestrian exposure to road crash. The effect of trip purpose on pedestrian crash was evaluated by disaggregating the pedestrian exposure proxies by purpose. Three random-parameter negative binomial regression models were developed to compare the performances of the three pedestrian exposure proxies. It was found that the model in which walking frequency was used as the exposure proxy provided the best goodness-of-fit. Frequency of walking back home, among other trip purposes, was the most sensitive to the increase in pedestrian crash risk. Additionally, increase in the frequency of pedestrian crash was correlated to the increases in the proportions of children and elderly people. Furthermore, household size, median household income, road density, number of non-signalized intersection as well as number of zebra crossings also significantly affected the pedestrian crash frequency. Findings of this study should be indicative to the development and implementation of effective traffic control and management measures that can improve the pedestrian safety in the long run.
行人在道路事故中容易受到重伤和死亡。了解行人事故的本质对于制定有效的安全对策和提高社会福利水平非常重要。有必要衡量暴露程度以量化行人事故风险。本研究的主要目的是探索有效的行人事故暴露度量方法,并确定可能导致行人事故发生的因素。在本研究中,基于 2011 年的出行特征调查(TCS)数据估算出行量,同时从香港运输署的交通信息系统(TIS)中获取 2011 年至 2015 年期间的事故数据。总人口、步行频率和步行时间被用来代表行人在道路事故中的暴露程度。通过按目的对行人暴露的代理变量进行细分,评估出行目的对行人事故的影响。建立了三个随机参数负二项回归模型,以比较三个行人暴露代理变量的性能。结果表明,以步行频率作为暴露代理的模型提供了最佳的拟合优度。在其他出行目的中,步行回家的频率对行人事故风险的增加最为敏感。此外,行人事故频率的增加与儿童和老年人比例的增加相关。此外,家庭规模、家庭中位数收入、道路密度、无信号交叉口数量以及斑马线数量也显著影响行人事故频率。本研究的结果应该对制定和实施有效的交通控制和管理措施具有指示意义,从长远来看可以提高行人的安全性。