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A comparative analysis of factors influencing the injury severity of daytime and nighttime crashes on a mountainous expressway in China

This study focuses on analyzing the injury severity of crashes occurring at different times of the day and providing insights into crash prevention countermeasures. The data contained 1521 police-reported crashes that occurred on a mountainous expressway between 2012 and 2017, which were divided int...

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Bibliographic Details
Published in:International journal of injury control and safety promotion 2021-12, Vol.28 (4), p.503-512
Main Authors: Peng, Zhipeng, Wang, Yonggang, Wang, Longjian
Format: Article
Language:English
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Summary:This study focuses on analyzing the injury severity of crashes occurring at different times of the day and providing insights into crash prevention countermeasures. The data contained 1521 police-reported crashes that occurred on a mountainous expressway between 2012 and 2017, which were divided into two subsamples: the daytime crash sample and the nighttime crash sample. The statistical plausibility of developing separate models for the two subsamples was verified by the likelihood ratio test. Two random thresholds random parameters hierarchical ordered probit models were independently conducted to analyze the relationship between injury severity and risk factors. The results showed that the contributing factors to injury severity were different between the two subsamples. The three factors most likely to cause serious crashes during the daytime were 'not keep a safe distance', 'drunk driving' and 'adverse weather', while during the nighttime, these three factors were 'fatigued driving', 'adverse weather' and 'drunk driving'. The same factors can cause more serious consequences during the nighttime than that during the daytime. After fully identifying the contributing factors related to injury severity, and in particular distinguishing the features of daytime and nighttime crashes, some useful suggestions were proposed to mitigate crash injury severity.
ISSN:1745-7300
1745-7319
DOI:10.1080/17457300.2021.1964089