Examining Prominent Causes of Traffic Injury Severity in Louisiana with Multinomial Logistic Models

多项式logistic回归 撞车 毒物控制 伤害预防 逻辑回归 职业安全与健康 人为因素与人体工程学 自杀预防 法律工程学 运输工程 环境卫生 人口学 工程类 心理学 地理 医学 计算机科学 统计 数学 病理 社会学 内科学 程序设计语言
作者
Onyumbe Lukongo
出处
期刊:Transportation Research Record [SAGE]
卷期号:2675 (1): 245-257 被引量:3
标识
DOI:10.1177/0361198120964786
摘要

Accidents rank third among the top 10 leading causes of death in Louisiana, claiming more than 2,000 lives out of a total of almost 33,000 deaths. Drivers’ characteristics (age and gender), the geometry of the roadways, driving on the major roadways, the day of the week, and the wet or dry condition or the road have been associated with crash severity. This study applies unordered multinomial logistic models to investigate causes leading to crash severity in Louisiana. Several models were estimated and the best results were retained for presentation and discussion. Consistent with previous research, findings suggest that drivers’ gender and age matter for traffic safety. Individually, male and older drivers are too risky. Major roads, weekdays, dry surfaces, and road geometry increase the risk of fatal accidents. Male drivers are prone to severe and fatal accidents while old drivers are vulnerable to all types of accidents. Young drivers and female drivers feature among cases of injury and moderate accidents. Evidence suggests that crash severity is not ethnicity specific, contrary to some studies. This study is relevant because it builds a new dataset for safety research, identifies risk factors, and informs the aim of public safety policy to reduce loss of life, injuries, and costs resulting from motor vehicle accidents.

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