Modelling risky driving behaviour

Abstract


 
 
 This paper aims to demonstrate that advanced technique of modelling may provide insights and improve our understanding of driver behavior in risky decision-making situations. The paper introduces a Hybrid choice model in order to explain the overtaking decision on two-lane highways, which is well known as a risky decision in the safety literature. This model integrates a latent variable model and an overtaking choice model by combining their measurement and structural equations. Specifically, the paper investigates the role of four personality latent variables: Thrill and Adventure Seeking, Boredom Susceptibility, Geographic Ability, and Driving Anger. Respondents to a web-based survey ranked their likelihood to overtake on two-lane highways; two scenarios were captured via short videos: the first presenting a straight section of a road with good visibility, and the second approaching a curve with reduced visibility. Several indicators were collected via self-reported questionnaire. Results indicate that, two out of the four personality latent variables investigated, Thrill and Adventure Seeking and Geographic Ability provide significant explanation for overtaking decision. Both of them are positively correlated with higher risky overtaking behavior. The Hybrid model, by considering latent variables alongside observable variables and attributes of the decision, enhances the comprehension of overtaking behaviour, and therefore may be deployed for explaining other decisions related to risky driving behaviour.