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研究手动和自动变速器车辆碰撞事故中驾驶员的损伤严重程度:均值和方差具有异质性的随机参数混合逻辑模型。

Examining drivers injury severity for manual and automatic transmission vehicles-involved crashes: Random parameter mixed logit model with heterogeneity in means and variances.

作者信息

Atombo Charles

机构信息

Department of Mechanical Engineering, Department of Civil Engineering, Ho Technical University, P.O. Box HP217, Ho, Ghana.

出版信息

Heliyon. 2024 Aug 19;10(16):e36555. doi: 10.1016/j.heliyon.2024.e36555. eCollection 2024 Aug 30.

Abstract

The effect of vehicle transmission type on driver injury severities have not been thoroughly studied. The study used four-year historical crash data that occurred between the year 2019 and 2022 in Ghana. The data shows 1856 and 2272 crashes for automatic and manual transmission, respectively. The study examined the factors influencing driver injury severity in crashes involving vehicles with manual and automatic transmissions, using Random Parameter Mixed Logit Model to account for heterogeneity in the dataset. It was observed that use of manual transmission is related to a higher risk of incapacitating and fatal injuries compared to automatic transmission. Specifically, for automatic transmission vehicle-involved crashes, factors related to fatal injury were overaged vehicles, public transport, morning and evening peak hours, head-on and rollover crashes. Crashes involving saloon cars and low age cars were associated with incapacitating injury whiles rainy weather condition was related to both fatal and incapacitant injuries. Regarding manual transmission, fatal injury was associated with crashes involving male and novice drivers, cars, pickup trucks, HGV, public transports, morning and evening peak hours, rainy weather conditions and curved roads. Also, buses, private cars and trip distance were related to incapacitating injury. The rollover crashes and overaged vehicles were also associated with both fatal and incapacitating injuries. Four random parameters demonstrated heterogeneity in means, with two factors influencing the variances of two parameters for automatic transmission model. For the manual transmission model, five random parameters showed heterogeneity in means, with four variables influencing the variances of three parameters. These findings are valuable for policymakers, manufacturers, and drivers in implementing targeted interventions and safety measures to promote road safety.

摘要

车辆传动类型对驾驶员受伤严重程度的影响尚未得到充分研究。该研究使用了2019年至2022年期间在加纳发生的四年历史碰撞数据。数据显示,自动变速器和手动变速器的碰撞事故分别为1856起和2272起。该研究使用随机参数混合逻辑模型来考虑数据集中的异质性,研究了涉及手动和自动变速器车辆碰撞中影响驾驶员受伤严重程度的因素。研究发现,与自动变速器相比,使用手动变速器会导致更高的致残和致命伤害风险。具体而言,对于涉及自动变速器车辆的碰撞事故,与致命伤害相关的因素包括老旧车辆、公共交通、早晚高峰时段、正面碰撞和翻车事故。涉及轿车和低龄汽车的碰撞事故与致残伤害有关,而雨天天气状况与致命和致残伤害均有关。对于手动变速器,致命伤害与涉及男性和新手驾驶员、汽车、皮卡、重型货车、公共交通、早晚高峰时段、雨天天气状况和弯道的碰撞事故有关。此外,公交车、私家车和行驶距离与致残伤害有关。翻车事故和老旧车辆也与致命和致残伤害均有关。四个随机参数在均值上表现出异质性,有两个因素影响自动变速器模型中两个参数的方差。对于手动变速器模型,五个随机参数在均值上表现出异质性,有四个变量影响三个参数的方差。这些发现对于政策制定者、制造商和驾驶员实施有针对性的干预措施和安全措施以促进道路安全具有重要价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3175/11388684/ed5f9d86dd64/gr1.jpg

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