昼夜骑自行车者在车辆/自行车碰撞中受伤严重程度的分析:无约束和部分约束时间建模方法的比较

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Analytic Methods in Accident Research Pub Date : 2023-09-09 DOI:10.1016/j.amar.2023.100301
Nawaf Alnawmasi , Fred Mannering
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引用次数: 3

摘要

由于能见度限制和其他因素,骑自行车的人在夜间车辆和自行车碰撞中所受的伤害往往比白天更严重。本文试图通过研究新冠肺炎封锁之前、期间和之后发生的撞车事故中,日间/夜间骑自行车者的伤害严重程度如何变化,来深入了解这种日间/夜间伤害严重程度现象。使用佛罗里达州三年期间(2019年至2021年,包括2019年)的车辆-自行车碰撞数据,使用随机参数logit方法估计了骑自行车者损伤严重程度的单独年度模型(包括严重损伤、轻微损伤和无可见损伤的可能结果),随机参数的均值和方差可能存在异质性。进行了似然比测试,以检查研究年份内模型估计的总体稳定性以及昼夜差异,并对部分约束和无约束的时间建模方法进行了比较。考虑了一系列可能影响车辆/自行车碰撞中骑车人受伤严重程度的变量,包括骑车人和车辆驾驶员信息、车辆特征、道路和环境条件、时间特征和道路特征。研究结果显示,在新冠肺炎大流行之前、期间和之后,白天和夜间的损伤严重程度存在统计学显著差异。样本外模拟结果表明,通过强制反射率、改善道路照明、开展与夜间骑自行车者安全相关的公众宣传活动以及车辆中易受伤害的道路使用者检测传感器来提高骑自行车者的能见度,都有助于大幅提高夜间骑自行车的安全性。
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An analysis of day and night bicyclist injury severities in vehicle/bicycle crashes: A comparison of unconstrained and partially constrained temporal modeling approaches

Due to visibility limitations and other factors, the injuries sustained by bicyclists in nighttime vehicle-bicycle crashes tend to be more severe than daytime crashes. This paper seeks to provide insights into this day/night injury severity phenomenon by studying how day/night bicyclist injury severities have changed in crashes that occurred before, during, and after the COVID-19 lock downs. Using data from vehicle-bicycle crashes in the state of Florida over a three-year period (from 2019 to 2021 inclusive), separate yearly models of bicyclist-injury severities (with possible outcomes of severe injury, minor injury, and no visible injury) were estimated using a random parameters logit approach with possible heterogeneity in the means and variances of random parameters. Likelihood ratio tests were conducted to examine the overall stability of model estimates across the studied years as well as day/night differences, and a comparison of partially constrained and unconstrained temporal modeling approaches was undertaken. A wide range of variables potentially affecting resulting bicyclist injury severities in vehicle/bicycle crashes was considered including bicyclist and vehicle driver information, vehicle features, roadways and environmental conditions, temporal characteristics, and roadway features. The findings show statistically significant injury-severity differences between daytime and nighttime before, during and after the COVID-19 pandemic. Out-of-sample simulation results suggest that improving the visibility of bicyclist through mandated reflectivity, improved roadway illumination, undertaking public awareness campaigns relating to nighttime bicyclist safety, and vulnerable road user detection sensors in vehicles can all contribute to substantially improving nighttime bicyclist safety.

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来源期刊
CiteScore
22.10
自引率
34.10%
发文量
35
审稿时长
24 days
期刊介绍: Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.
期刊最新文献
Editorial Board A cross-comparison of different extreme value modeling techniques for traffic conflict-based crash risk estimation The role of posted speed limit on pedestrian and bicycle injury severities: An investigation into systematic and unobserved heterogeneities Investigating work-related distraction’s impact on male taxi driver safety: A hazard-based duration model Rethinking cycling safety: The role of gender in cyclist crash injury severity outcomes
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