Seasonal variations and temporal instability of motorcyclist injury severity in Cambodia: Analyses based on a random parameter logit model with heterogeneity in means and variances

柬埔寨摩托车骑行者受伤严重程度的季节性变化和时间不稳定性:基于均值和方差异质性的随机参数logit模型的分析

阅读:1

Abstract

Motorcycles are a prevalent mode of transportation in countries like Cambodia that experience distinct rainy and dry seasons. However, the safety concerns associated with motorcycling in this region have not been thoroughly investigated. This study addresses this research gap by examining the severity of motorcyclist injuries in Cambodia, considering the potential variations across seasons and the fluctuations in contributing factors over time. Utilizing a random parameter logit model with heterogeneity in means and variances, the research analyzes motorcycle crash data from 2015 to 2017 to identify heterogeneities in the determinants of injury severity. The study confirms seasonal variations and temporal instabilities in influential factors, highlighting the need for distinct modeling for dry and rainy seasons due to varying contributing factors. Key findings include the consistent increase in fatal injury risk associated with head-on collisions and elderly rider involvement across both seasons. During the rainy season, motorcycle-to-motorcycle crashes significantly heighten the likelihood of severe injuries, with weekend crashes more likely to result in fatalities. Furthermore, more than half of speeding incidents during the rainy season consistently led to fatal injuries across all three years. In contrast, during the dry season, riders faced a greater risk of severe injuries compared to pillion riders, with crashes on national roads more likely to lead to fatal outcomes. Temporal stability tests further reveal that the influence of external variables on motorcyclist injury severity varies across years, stressing the need for tailored, season-specific approaches to effectively mitigate and prevent crashes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。