Identifying key patterns in motorcycle crashes: findings from taxicab correspondence analysis

Abstract

ABSTRACT Due to the absence of protective structural surrounding and advanced restraints like the motorists, motorcyclists are considered vulnerable roadway users like pedestrians and bicyclists. Per vehicle mile traveled in 2016, motorcyclist fatalities occurred 28 times more frequently than passenger car occupant fatalities. The identification of the patterns and associations between key contributing factors can help in determining strategies for motorcycle-related crash reduction. In addition to current endeavors, there is a need for newer directions in study design with newer data sources and methods. Determining the groups of core factors helps address motorcycle crashes more effectively. This study used seven years (2010–2016) of motorcycle crash data in Louisiana to determine the key relationships between the influencing factors by using Taxicab Correspondence Analysis (TCA). The analysis showed that TCA presents a dimension-reduced map of the variable categories by developing several clusters.