• December 13th, 2018

This document reports the results of a study to determine on average over a large number of cases, which driver is more apt to be at fault in two-vehicle crashes that involve two types of drivers (e.g., large truck and car; car and pedestrian, car and bicycle, car and motorcycle, etc.). This information is essential to effective countermeasure development with regard to changing driver behavior since ignoring who it typically at fault could lead to a miss-allocation of resources (e.g., targeting truck drivers, when cars are most often at fault).

For this study, traffic crash data were obtained from data that included the 2009-2013 calendar years. The officer’s opinion as to which driver was at-fault (also referenced as the causal driver) is a data element in the crash record. Records without an officers’ indications of the unit that caused the crash were omitted. In order to make a fair comparison it was necessary to create subsets of the data that did not bias the data in either direction. For example, all single-vehicle crashes were omitted from consideration. For the comparison to be valid one of the units had to be of one type (e.g., truck) and the other of the second type (e.g., passenger cars and other nontruck vehicles). This led to a fair comparison and a clean estimate of the relative frequency (i.e., the probability) of a given unit or driver type causing the category of crash under consideration.