TY  - JOUR
PY  - 2021//
TI  - A correlated random parameters with heterogeneity in means approach of deer-vehicle collisions and resulting injury-severities
JO  - Analytic methods in accident research
A1  - Ahmed, Sheikh Shahriar
A1  - Cohen, Jessica
A1  - Anastasopoulos, Panagiotis Ch.
SP  - 100160
EP  - 100160
VL  - 30
IS  - 
N2  - This paper investigates deer-vehicle collisions and their resulting injury-severities in a threefold approach. Two random parameters binary logit models with heterogeneity in means are estimated to analyze: (a) the likelihood of witnessing deer on the roadway; and (b) the likelihood of a vehicle hitting deer on the roadway. Additionally, a novel variant of ordered probability models, namely the correlated random parameters ordered logit model with heterogeneity in means, is estimated to explore the factors contributing to different driver injury-severity outcomes resulting from deer-vehicle collisions. A database of crashes maintained by the Pennsylvania Department of Transportation for the year 2018 is used for the analysis. The findings reveal that it is more likely to witness deer in rural locations, in dark lighting conditions, and during deer breeding season - when deer are more active in moving from one location to another. In addition, it is more likely for vehicles to hit deer in roads with speed limits above 55 mph, and during the deer breeding season. Furthermore, female drivers are found to be more likely to hit deer as compared to male drivers. Finally, airbag deployment and post-crash overturning of the vehicle are both associated with major injuries and fatalities; whereas, use of restraints is found to prevent injuries or fatalities. Employing the correlated random parameters and the heterogeneity in means approaches offers additional insights about the effects of unobserved heterogeneity on factors contributing to the likelihood of witnessing and hitting deer on the roadway, as well as the driver injury-severity levels resulting from deer-vehicle collisions.<p />  <p>Language: en</p>
LA  - en
SN  - 2213-6657
UR  - http://dx.doi.org/10.1016/j.amar.2021.100160
ID  - ref1
ER  -