揭示不同年龄组和不同时间段伤害严重程度的决定因素:深入探究行人碰撞事故中的非观测异质性

IF 12.5 1区 工程技术 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Qingli Liu, Fan Li, Kam K.H. Ng
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引用次数: 0

摘要

行人特别容易受到道路交通事故的影响,其受伤严重程度受年龄和时间变化的影响各不相同。本研究旨在调查影响不同年龄段行人受伤严重程度的因素的差异和时间变化。为此,我们采用了三个随机参数二元 Logit 模型,其均值(和方差)具有异质性。本研究采用了香港四年的行人碰撞数据。根据联合国对年轻人和老年人的定义,行人被分为三组:年轻人(25 岁以下)、中年人(25-65 岁)和老年人(65 岁以上)。最初的似然比测试表明,2019 年至 2021 年期间,年轻组具有时间稳定性,在整合了三年的年轻数据后,进一步的测试证实了年龄可转移性和整体时间稳定性。随后又开发了部分约束时间稳定性方法,以进一步捕捉单个变量的时间稳定性并简化模型结果。模型结果确定了影响行人受伤严重程度的因素,包括行人、驾驶员、车辆、时间和光照条件特征。一些影响因素表现出年龄转移性或时间稳定性,例如受控交叉路口、近受控交叉路口、注意力不集中的驾驶员和私家车。然而,大多数诱因的重要性在不同年龄组和不同年份有所不同,某些因素具有特定年龄或特定年份的特点。样本外预测强调了致命或严重伤害随着年龄增长而累积的可能性,与其他两个年龄模型相比,中年模型在伤害严重性风险方面表现出最高的时间稳定性。此外,在 COVID-19 封锁的第一年(2020 年),香港的中年行人面临的致命或严重伤害风险最高,但在随后的一年中,所有年龄组的行人面临的风险都显著下降。根据这些研究结果,提出了考虑年龄差异的针对性预防措施,以有效提高行人安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unveiling the determinants of injury severities across age groups and time: A deep dive into the unobserved heterogeneity among pedestrian crashes

Pedestrians, particularly susceptible to road traffic crashes, experience varying injury severities influenced by age and time shifts. This research aims to investigate the differences and temporal shifts in factors influencing pedestrian injury severities across different age groups. To achieve this, three random parameters binary logit models with heterogeneity in the means (and variances) were employed. Four years of pedestrian crash data in Hong Kong were utilized in this study. According to United Nations’ definitions of the young and elderly, pedestrians were categorized into three groups: young (under 25 years old), middle-aged (25–65 years old), and elderly (over 65 years old). Initial likelihood ratio tests indicated temporal stability in the young group between 2019 and 2021, with further tests confirming age transferability and overall temporal stability after integrating the three years of young data. The partially constrained temporal stability approach was then developed to further capture the temporal stability of individual variables and simplify model results. Model results identified factors impacting pedestrian injury severities, encompassing pedestrian, driver, vehicle, temporal, and light condition characteristics. Some contributing variables exhibit age-transferability or temporal stability, such as controlled crossing, near controlled crossing, inattentive driver and private car. However, the significance of most contributors varies across age groups and years, with certain factors being age-specific or year-specific. Out-of-sample predictions underscore the cumulative likelihood of fatal or severe injuries with advancing age, and the middle-aged models showed the highest level of temporal stability regarding the risk of injury severity compared to the other two age models. Moreover, middle-aged pedestrians in Hong Kong faced the highest risk of fatal or severe injuries during the first year of the COVID-19 lockdown (2020), but the risk significantly declined for pedestrians of all age groups in the subsequent year. Based on these findings, targeted preventive measures that take into account age differences have been proposed to effectively enhance pedestrian 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.
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