Driving Behavior Analysis Based on Weighted Cost Function

Abstract

Drivers are the main participants of road traffic, and analyzing their driving behavior characteristics is beneficial to road safety and personalized vehicle insurance formulation. Most existing studies describe driving behavior characteristics by constructing various driving behavior features of driving data. However, drivers' pursuit of different property is the main reason to form different driving behavior characteristics. Therefore, this paper proposes a novel framework, which uses the weight of cost function to represent driving behavior characteristics. Firstly, for every driver’s basic driving maneuver, cost function representing comfort, safety and quickness is calculated. Secondly, for every driver, weights of each characteristic are calculated by entropy weight method. Finally, based on these weights, driving style is clustered by k-means. Different than those previous studies can only describe driving behavior characteristics from results, this paper describes driving behavior characteristics from causes. Therefore, the framework proposed in this paper is helpful to deeply understand differences between various driving behavior characteristics, and beneficial for describing driver decision making. The empirical results on driving data implies that this framework can efficiently recognize driving behavior characteristics.