Modeling distraction tendency of motorized two-wheeler drivers in time pressure situations

Abstract

Distraction and Time Pressure (TP) are the two major contributors leading to driving performance degradation and crashes. Previous research conducted on distraction and TP mainly focused on car drivers of High-Income Countries and limited studies explored the effects of both conditions on Motorized Two-Wheeler (MTW) drivers of Low-and-Middle-Income Countries. This study evaluates distraction tendency of MTW drivers in TP situations based on psychological, socioeconomic, and demographic factors along with vehicle characteristics. A total of 513 responses were collected through an online survey. The questionnaire focused on MTW drivers’ perception regarding distraction tendency and psychological (subjective norm, motivation for distraction, perceived risk, and attitude and behavior) along with other factors. Initially, Structural Equation Modeling (SEM) was conducted to obtain a relation between distraction tendency and psychological factors. Finally, Ordered Logistic Regression (OLR) models were developed to quantify the influence of various factors and TP situations on distraction tendencies such as talking to pillion rider, conversation and texting on mobile phones while driving. The SEM revealed that motivation for distraction and attitude and behavior was positively related to distraction tendencies under the TP driving situation. Further, the OLR model results showed that the odds of distraction due to mobile phone conversation, texting, and talking to pillion rider reduced by 48%, 33%, and 77%, respectively when the drivers were under TP situation. This study also revealed that MTWs with lower engine sizes, mostly present in Low-and-Middle-Income Countries, had 22% more chances of distraction due to conversation on mobile phones. It was observed that perceived risk had no significant influence on the distraction tendency of the drivers. Therefore, it is important to consider the intervention of psychological factors beyond perceived risk while making policies for reducing distracted driving patterns.