Study on Assessing Drivers' Comprehensive Quality Based on CAN Data

Abstract

Annually, there are thousands of traffic accidents casually in the world, so it is extremely important to research behavior of drivers in current days. To achieve it, we set up a platform to gather CAN data from vehicles independently. In this paper, three assessment indexes such as driving safety, riding comfort and fuel consumption of vehicles were put forward for assessing drivers’ comprehensive quality based on CAN data. This paper analyzed these indexes from the entropy of steering wheel angle, vehicle speed and other 7 factors. Firstly, this paper used FAHP to establish a single factor weight vector. Then the paper calculated the single factor fuzzy judgment matrix by membership functions. Finally, we assessed the driver's comprehensive quality by maximum membership. The practices proved that this model provides a simple and effective for assessing the comprehensive quality of drivers.