Wang Chenzhu, Abdel-Aty Mohamed, M Easa Said, Chen Fei, Cheng Jianchuan, Jamal Arshad
School of Transportation, Southeast University, Nanjing, China.
Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, Florida, USA.
Traffic Inj Prev. 2024;25(4):623-630. doi: 10.1080/15389588.2024.2331644. Epub 2024 Mar 28.
A lower helmet-wearing rate and overspeeding in Pakistan are critical risk behaviors of motorcyclists, causing severe injuries. To explore the differences in the determinants affecting the injury severities among helmeted and non-helmeted motorcyclists in motorcycle crashes caused by overspeeding behavior, single-vehicle motorcycle crash data in Rawalpindi city for 2017-2019 is collected. Considering three possible crash injury severity outcomes of motorcyclists: fatal injury, severe injury and minor injury, the rider, roadway, environmental, and temporal characteristics are estimated.
To provide a mathematically simpler framework, the current study introduces parsimonious pooled random parameters logit models. Then, the standard pooled random parameters logit models without considering temporal effects are also simulated for comparison. By comparing the goodness of fit measure and estimation results, the parsimonious pooled random parameters logit model is suitable for capturing the temporal instability. Then, the non-transferability among helmeted and non-helmeted overspeeding motorcycle crashes is illustrated by likelihood ratio tests and out-of-sample prediction, and two types of models provide robust results. The marginal effects are also calculated.
Several variables, such as age, cloudy and weekday indicators illustrate temporal instability. Moreover, several variables are observed to only show significance in non-helmeted models, showing non-transferability across helmeted and non-helmeted models.
More educational campaigns, regulation and enforcement, and management countermeasures should be organized for non-helmeted motorcyclists and overspeeding behavior. Such findings also provide research reference for the risk-compensating behavior and self-selected group issues under overspeeding riding considering the usage of helmets.
在巴基斯坦，较低的头盔佩戴率和超速是摩托车骑手的关键风险行为，会导致严重伤害。为了探究在因超速行为导致的摩托车碰撞事故中，影响佩戴头盔和未佩戴头盔的摩托车骑手受伤严重程度的决定因素的差异，收集了2017 - 2019年拉瓦尔品第市的单车摩托车碰撞数据。考虑摩托车骑手三种可能的碰撞伤害严重程度结果：致命伤、重伤和轻伤，对骑手、道路、环境和时间特征进行了评估。
为了提供一个数学上更简单的框架，本研究引入了简约合并随机参数逻辑模型。然后，还模拟了不考虑时间效应的标准合并随机参数逻辑模型以作比较。通过比较拟合优度指标和估计结果，简约合并随机参数逻辑模型适用于捕捉时间不稳定性。然后，通过似然比检验和样本外预测说明了佩戴头盔和未佩戴头盔的超速摩托车碰撞事故之间的不可转移性，两种模型都提供了稳健的结果。还计算了边际效应。
几个变量，如年龄、阴天和工作日指标显示出时间不稳定性。此外，观察到几个变量仅在未佩戴头盔的模型中显示出显著性，表明在佩戴头盔和未佩戴头盔的模型之间不可转移。
应该为未佩戴头盔的摩托车骑手和超速行为组织更多的教育活动、监管与执法以及管理对策。这些发现也为考虑头盔使用情况的超速骑行下的风险补偿行为和自我选择群体问题提供了研究参考。
