建成环境对老年人交通事故严重程度异质性影响

为量化建成环境因素对事故伤害严重程度的影响，本文构建基于均值和方差异质性的随机参数Logit模型对老年人交通事故伤害严重程度进行异质性分析。采用2019年美国某州老年人交通事故数据，从老年人特性、车辆特性、道路特性、道路环境特性、建成环境特性这5个方面选取17个影响因素，利用平均弹性系数捕捉各因素对事故伤害严重程度的影响。结果表明：基于均值和方差异质性随机参数Logit模型的拟合优度更高；建成环境因素中事故发生地300 m缓冲区 内存在购物中心为随机变量，其均值与男性老年人、车道数为3显著相关，方差与道路控制方式为未控制显著相关；摩托车、直线、湿润等因素显著增加了老年人交通事故伤害严重程度。研究结果有助于交通管理者采取适当的策略降低老年人交通事故伤害严重程度。

Heterogeneous Effects of Built Environment on Elderly Traffic Accident Injury Severities

This paper uses a random parameter approach with heterogeneity in means and variances to analyze the heterogeneity of elderly traffic accident injury severities. The 2019 traffic accident data in a state of the United States is used for the analysis. 17 influencing factors are selected based on the characteristics of elderly, vehicle, road, road environment, and built environment. The average elasticity coefficient is used to reflect the effect of each factor on the accident injury severities. The results show that the goodness of fit of Logit model based on mean and variance heterogeneity random parameter is better than traditional method. Among the built environment factors, the existence of a shopping center in the 300-meter buffer zone was a random variable. Its mean value was significantly correlated with the male elderly and the number of lanes with the coefficient of 3. The variance was significantly correlated with the uncontrolled road control mode. In addition, motorcycle, tangent segment, wet road surface and other factors significantly increased the severity of injury severities. The results of this study provide refences for policy makers to adopt appropriate strategies to reduce the severity of elderly traffic accident injuries.