Citation

Xie K, Ozbay K, Yang H. Traffic Injury Prev. 2018; 19(2): 189-194.

Affiliation

Department of Modeling , Simulation & Visualization Engineering, Old Dominion University , Norfolk , Virginia.

Copyright

(Copyright © 2018, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2017.1369530

PMID

29058459

Abstract

OBJECTIVE: This study aims to investigate the contributing factors to secondary collisions and the effects of secondary collisions on injury severity levels. Manhattan, which is the most densely populated urban area of New York City, is used as a case study. In Manhattan, about 7.5% of crash events become involved with secondary collisions and as high as 9.3% of those secondary collisions lead to incapacitating and fatal injuries.

METHODS: Structural equation models (SEMs) are proposed to jointly model the presence of secondary collisions and injury severity levels and adjust for the endogeneity effects. The structural relationship among secondary collisions, injury severity, and contributing factors such as speeding, alcohol, fatigue, brake defects, limited view, and rain are fully explored using SEMs. In addition, to assess the temporal effects, we use time as a moderator in the proposed SEM framework.

RESULTS: Due to its better performance compared with other models, the SEM with no constraint is used to investigate the contributing factors to secondary collisions. Thirteen explanatory variables are found to contribute to the presence of secondary collisions, including alcohol, drugs, inattention, inexperience, sleep, control disregarded, speeding, fatigue, defective brakes, pedestrian involved, defective pavement, limited view, and rain. Regarding the temporal effects, results indicate that it is more likely to sustain secondary collisions and severe injuries at night.

CONCLUSIONS: This study fully investigates the contributing factors to secondary collisions and estimates the safety effects of secondary collisions after adjusting for the endogeneity effects and shows the advantage of using SEMs in exploring the structural relationship between risk factors and safety indicators. Understanding the causes and impacts of secondary collisions can help transportation agencies and automobile manufacturers develop effective injury prevention countermeasures.

Language: en

Keywords

Safety analysis; endogeneity; injury severity; secondary collisions; structural equation model; structural relationship; urban area