Citation

Duddu VR, Penmetsa P, Pulugurtha SS. Accid. Anal. Prev. 2018; 120: 55-63.

Affiliation

Civil & Environmental Engineering Department / IDEAS Center, The University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC, 28223-0001, USA. Electronic address: sspulugurtha@uncc.edu.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.aap.2018.07.036

PMID

30086438

Abstract

This paper examines and compares the effect of selected variables on driver injury severity of, both, at-fault and not at-fault drivers. Data from the Highway Safety Information System (HSIS) for the state of North Carolina was used for analysis and modeling. A partial proportional odds model was developed to examine the effect of each variable on injury severity of at-fault driver and not at-fault driver, and, to examine how each variable affects these two drivers' injury severity differently. Road characteristics, weather condition, and geometric characteristics were observed to have a similar effect on injury severity in a crash to at-fault and not at-fault drivers. Age of the driver, physical condition, gender, vehicle type, and, the number and type of traffic rule violations were observed to play a significant role in the injury severity of not at-fault drivers when compared to at-fault drivers in the crash. Moreover, motorcyclists and drivers 70 years or older are observed to be the most vulnerable road users.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en

Keywords

At-fault; Crash; Driver; Injury severity; Not at-fault; Partial proportional odds model