Citation

Hamzeie R, Savolainen PT. Transp. Res. Circular 2017; (E-C221): pp 14-23.

Copyright

(Copyright © 2017, U.S. National Academy of Sciences Transportation Research Board)

DOI

unavailable

PMID

unavailable

Abstract

Multivehicle crashes resulted in more than 14,000 fatalities in 2013, which accounted for more than 40 percent of all traffic fatalities across the United States. In a majority of these crashes one or more of the crash-involved drivers were identified as being an at-fault driver, meaning that they performed a leading error that contributed to the crash occurrence. Research has generally shown that the characteristics and behaviors of such drivers are different from those of not-at-fault drivers. The purpose of this study was to identify the factors associated with at-fault and not-at-fault status in a multivehicle conflict. The Naturalistic Driving Study data that have been developed as part of the second Strategic Highway Research Program were utilized to further investigate these factors. Multivehicle conflicts, including both crash and near-crash events, were investigated in association with driver characteristics and behaviors that were captured through different surveys. Mixed-effect logistic regression models were developed to examine and compare a multitude of data elements including driver demographic information, risk perception, driving behaviors, and sleep habits. Consequently, the factors associated with fault status were identified using the detailed data. The findings revealed that full-time workers, drivers who perceive tailgating as being high risk, and those who were not involved in any crashes during the three years prior to the study were less likely to be at fault. On the other hand, the likelihood of being at fault was found to be noticeably higher among drivers who were less risk averse, including those who believed that accelerating at the onset of yellow is low risk, as well as for those drivers who feel fatigued nearly every day.

Language: en

Keywords

Drivers; Crash causes; Automatic data collection systems; Human factors in crashes; Multiple vehicle crashes; Strategic Highway Research Program 2