EVALUATION OF DRIVER’S ECO-DRIVING SKILLS BASED ON FUZZY LOGIC MODEL – A REALISTIC EXAMPLE OF VEHICLE OPERATION IN REAL-WORLD CONDITIONS

Abstract

It is well known that fuzzy logic is a processing tool in circumstances lacking of clear linguistic information, as well as making conclusions based on imprecise assertions and rough data. Eco-driving rules that the drivers should comply with are not always made of concrete values (exact acceleration / deceleration rates, torque or headway / distance kept from the vehicle ahead, etc.), but often linguistically expressed and subjective (e.g. soft acceleration, mid-range engine speed, soft deceleration, sufficient distance, etc.). Therefore, the authors recognized fuzzy logic potentials as an efficient tool to overcome all mentioned barriers and thus to increase vehicle energy eficiency and reduce emissions of harmful gases which are main goals of eco-driving. The primary objective of this paper is to raise the awareness on the potentials and efficiency of fuzzy logic systems’ use in eco-driving as a tool for achieving more ecologically & economically sustainable road transport. The rules that drivers should follow in order to achieve and maintain eco-driving goals, as well as the parameters to be monitored to evaluatedriver’s behaviour i.e. the compliance with eco-driving rules are presented in the paper. The authors propose a driver rating system based on the fuzzy logic model constructed within MatLab. Within the proposed model the input parameters are actual acceleration/deceleration rates, engine speed and accelerator pedal pressure(APP) and while model output are driver ratings (scores ranging from 0 to 10 points) after completed a driving cycle. A real-world example based on data collected via vehicle OBDII connector by a TEXA logging device in realistic vehicle operation conditions. The consequent actual results of drivers’ behaviour rating tool based on the proposed model are presented in the paper.