Data-driven Identification and Behavioral Assessment of Anxious Drivers Based on Fuzzy Analytic Hierarchy Processes

Abstract

A significant aspect of enhancing road safety is the understanding and recognition of anxious driving behavior. In this paper, we present a comprehensive approach to identifying and assessing anxious drivers by leveraging factor analytical techniques and fuzzy Analytic Hierarchy Processes (FAHP) based on the effective responses from the Driving Behavior Survey (DBS). The factor analysis results indicate that anxious driving behavior is a multi-dimensional construct, comprising multiple key factors such as aggressiveness, distraction, exaggerated caution and driving performance deficits. These dimensions are intricately interconnected and collectively contribute to the overall assessment of a driver's anxious behavior. By utilizing the weights determined through the implementation of the FAHP method on the factor structure, the anxiety ratings for individual drivers generated from our data-driven approach provide invaluable information for various stakeholders, including traffic safety authorities, insurance companies, and drivers themselves.