Validating measures of driver behavior’s training factors for prime decision-making

Abstract

This paper validates the Driver Behavior’s Training Instrument (BDTI) for measuring training factors that influence prime decision-making in a driving domain. First, the training factors were developed to evaluate Computational Rabi’s Driver Training (C-RDT) model for prime decision-making in driving. In order to validate the model, a three-phase validation method has been used in this paper. In the first phase, items were generated from the literature to measure driver behavior’s training factors. In the 2nd phase, 4 academic experts and 3 experts from a driving institution were consulted for face and content validity. A Content Validity Index (CVI) of both the items-level and the scale-level CVIs was conducted from the ratings of the seven (7) experts. Finally, the items were subjected to a reliability test and an Exploratory Factor Analysis (EFA) with Varimax rotation in the 3rd phase. The findings presented in this study revealed 10 valid scales for measuring driver behavior’s training factors namely; basic skills, basic practice, sensory ability, driving goal, driving intention, potential hazardous information, exposure to task complexity, perception about risk, driving knowledge, and involuntary/voluntary automaticity. The scales validated in this paper should assist other model developers; particularly driver behavior’s training modelers to validate their factors for prime decision-making. In literature the measures of driver behavior and training factors that influence drivers’ prime decision are limited. Hence, this paper considers the validation of driver behavior’s training instrument that measures the training factors for prime decision-making important.