Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach.

Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach. Int J Inj Contr Saf Promot. 2019 Nov 13;:1-12 Authors: Čubranić-Dobrodolac M, Švadlenka L, Čičević S, Dobrodolac M Abstract This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver's psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver's propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the pr...
Source: International Journal of Injury Control and Safety Promotion - Category: Accident Prevention Tags: Int J Inj Contr Saf Promot Source Type: research