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Examining injury severity in truck-involved collisions using a cumulative link mixed model.
Journal of Transport & Health ( IF 3.613 ) Pub Date : 2020-09-10 , DOI: 10.1016/j.jth.2020.100942
Mingyang Chen 1 , Peng Chen 2 , Xu Gao 3 , Chao Yang 1
Affiliation  

Background

Trucks play a vital role in promoting regional freight transportation and economic development, but truck-involved collisions often have more severe consequences and create greater losses for society.

Research purpose

This study examined the relationships between injury severity and various explanatory factors in truck-involved collisions to identify preventive countermeasures for safety improvement.

Data

Los Angeles’ collision records from 2010 to 2018 were analyzed.

Method

A cumulative link mixed model was applied, where the heterogeneities among drivers were highlighted.

Result

Our findings confirmed that various driving mistakes, such as speeding, improper driving, and drinking alcohol, contributed to severe injuries. Male drivers were more likely to be severely injured, while female occupants were more likely to be severely injured. The use of safety equipment always helped mitigate injury severity. Collisions at night on dark roads with no streetlights and collisions on slippery road surfaces had higher risks of causing severe injuries. In addition, collisions on ramps were more likely to result in severe injuries. Drivers in old trucks were also at a higher risk of suffering from severe injuries.

Conclusions

Freight companies are encouraged to monitor drivers’ performance using remote cameras. Policy-wise, local agencies should regulate improper driving behavior and safety equipment use for truck drivers. Improving lighting conditions, periodically testing the skid resistance of road surfaces, adjusting speed limits, and applying weigh-in-motion technologies may greatly help mitigate injury severity. Old trucks should be brought in for frequent tests or abandoned after many years of usage.



中文翻译:

使用累积链接混合模型检查卡车涉及的碰撞中的伤害严重程度。

背景

货车在促进区域货运和经济发展方面发挥着至关重要的作用,但货车碰撞事故往往造成的后果更加严重,给社会造成的损失也更大。

研究目的

本研究检查了卡车碰撞中伤害严重程度与各种解释因素之间的关系,以确定安全改进的预防对策。

数据

分析了 2010 年至 2018 年洛杉矶的碰撞记录。

方法

应用了累积链接混合模型,突出了驱动程序之间的异质性。

结果

我们的研究结果证实,各种驾驶错误,如超速、不当驾驶和饮酒,都会导致严重伤害。男性司机更容易受重伤,而女性乘客更容易受重伤。使用安全设备总是有助于减轻伤害的严重程度。夜间在没有路灯的黑暗道路上发生碰撞,以及在湿滑路面上发生碰撞,造成严重伤害的风险更高。此外,坡道上的碰撞更有可能导致严重伤害。旧卡车司机受重伤的风险也更高。

结论

鼓励货运公司使用远程摄像头监控司机的表现。在政策方面,地方机构应规范卡车司机的不当驾驶行为和安全设备使用。改善照明条件、定期测试路面的防滑性、调整速度限制以及应用动态称重技术可能会极大地帮助减轻伤害的严重程度。旧卡车应该被带进来进行频繁的测试或在使用多年后被丢弃。

更新日期:2020-09-10
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