Citation

Jalayer M, Pour-Rouholamin M, Zhou H. Traffic Injury Prev. 2018; 19(1): 35-41.

Affiliation

Department of Civil Engineering , Auburn University , Auburn , AL 36849-5337 , Tel.

Copyright

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

DOI

10.1080/15389588.2017.1347260

PMID

28657352

Abstract

OBJECTIVE: Wrong-way driving (WWD) crashes result in 1.34 fatalities per fatal crash, while for other non-WWD fatal crashes this number drops to 1.10. As such, further in-depth investigation of WWD crashes is necessary. The objective of this study is twofold: to identify the characteristics that best describe WWD crashes and to verify the factors associated with WWD occurrence.

METHODS: We collected and analyzed fifteen years of crash data from the states of Illinois and Alabama. The final dataset comprises 398 WWD crashes. The rarity of WWD events and the consequently small sample size of the crash database significantly influence the application of conventional log-linear models in analyzing the data, as they use maximum-likelihood estimation. To overcome this issue, in this study, we employ multiple correspondence analysis (MCA) to define the structure of the crash dataset and identify the significant contributing factors to WWD crashes on freeways.

RESULTS: The results of the present study specify various factors that characterize and influence the probability of WWD crashes, and can thus lead to the development of several safety countermeasures and recommendations. According to the obtained results, factors such as driver age, driver condition, roadway surface conditions, and lighting conditions were among the most significant contributors to WWD crashes.

CONCLUSIONS: Despite many other methods that identify only the contributing factors, this method can identify possible associations between various contributing factors. This is an inherent advantage of the MCA method, which can provide a major opportunity for state DOTs to select safety countermeasures that are associated with multiple safety benefits.

Language: en

Keywords

Wrong-way driving; contributing factors; multiple correspondence analysis; safety countermeasures