Driver behavior quantitative models: Identification and classification of variables

Abstract

In this paper we investigate driver behavior variables proposed in literature from an objective approach; we consider studies which employed numeric data that can be objectively measured by standardized tools and electronic devices, such as speed, acceleration and position. Our analysis develops in three phases; first we identify recent fields that focused on modeling driver behavior, such as Usage based insurance and governement agencies of transport. Next we extract quantitative variables from literature and classify them according to their importance; to achieve this, we identify their priority in each paper depending on their results. Finally we order them by their rate use in scientific literature, in order to have a comprehensive synthesis about the most significant and prevalent variables in literature. This paper therefore serves as reference for future studies on driver behavior; the collaboration we provide is a set of crucial variables for modeling, understanding and analysis driver behavior in quantitative research. Results show that “Speed”, “Acceleration/deceleration” and “Braking” are the most used in recent studies as well as considered priority variables.