Suppr超能文献

探究时间不稳定性对与十字路口及非十字路口相关碰撞事故中自行车骑行者受伤严重程度决定因素的影响。

Exploring temporal instability effects on bicyclist injury severities determinants for intersection and non-intersection-related crashes.

作者信息

Alnawmasi Nawaf, Ali Yasir, Yasmin Shamsunnahar

机构信息

Assistant Professor, Civil Engineering Department, College of Engineering, University of Ha'il, Hail 55474, Kingdom of Saudi Arabia.

School of Architecture, Building, and Civil Engineering, Loughborough University, Leicestershire LE11 3TU, United Kingdom.

出版信息

Accid Anal Prev. 2024 Jan;194:107339. doi: 10.1016/j.aap.2023.107339. Epub 2023 Oct 17.

Abstract

Cycling is a sustainable and healthy mode of transportation with direct links to reducing traffic congestion, lowering greenhouse gas emissions, and improving air quality. However, from a safety perspective, bicyclists represent a risky road user group with a higher likelihood of sustaining severe injuries when involved in vehicle crashes. With various determinants known to affect bicyclist injury severity and vary across locations, this study investigates the factors affecting bicyclist injury severity and temporal instability, considering the location of crashes. More specifically, the objective of this study is to understand differences in injury severities of intersection and non-intersection-related single-bicycle-vehicle crashes using four year crash data from the state of Florida. Random parameters logit models with heterogeneity in the means and variances are developed to model bicyclist injury severity outcomes (no injury, minor injury, and severe injury) for intersection and non-intersection crashes. Several variables affecting injury severities are considered in model estimation, including weather, roadway, vehicle, driver, and bicyclist characteristics. The temporal stability of the model parameters is assessed for different locations and years using a series of likelihood ratio tests. Results indicate that the determinants of bicyclist injury severities change over time and location, resulting in different injury severities of bicyclists, with non-intersection crashes consistently resulting in more severe bicyclist injuries. Using a simulation-based out-of-sample approach, predictions are made to understand the benefits of replicating driving behaviour and facilities similar to intersections for non-intersection locations, which could benefit in reducing bicyclist injury severity probabilities.

摘要

骑自行车是一种可持续且健康的交通方式,与减少交通拥堵、降低温室气体排放以及改善空气质量直接相关。然而,从安全角度来看,骑自行车的人是道路使用者中的一个风险群体,在发生车辆碰撞时更有可能遭受重伤。已知有多种因素会影响骑自行车者的受伤严重程度,且因地点而异,本研究考虑碰撞发生地点,调查影响骑自行车者受伤严重程度和时间不稳定性的因素。更具体地说,本研究的目的是利用佛罗里达州四年的碰撞数据,了解与十字路口和非十字路口相关的单车与车辆碰撞中受伤严重程度的差异。开发了均值和方差具有异质性的随机参数logit模型,以模拟十字路口和非十字路口碰撞中骑自行车者的受伤严重程度结果(无受伤、轻伤和重伤)。在模型估计中考虑了几个影响受伤严重程度的变量,包括天气、道路、车辆、驾驶员和骑自行车者的特征。使用一系列似然比检验评估模型参数在不同地点和年份的时间稳定性。结果表明,骑自行车者受伤严重程度的决定因素会随时间和地点而变化,导致骑自行车者受伤严重程度不同,非十字路口碰撞始终导致骑自行车者受伤更严重。使用基于模拟的样本外方法进行预测,以了解在非十字路口地点复制类似于十字路口的驾驶行为和设施的好处,这可能有助于降低骑自行车者受伤严重程度的概率。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验