Development of a trajectory following vehicle control model

Erdem Uzunsoy,Veysel Erkilic

doi:10.1177/1687814016650832

Abstract

Determination of the handling properties of a vehicle may be restrictive in some situations. A vehicle model coupled with a driver model may be necessary and even unavoidable to analyse the real road behaviour in the most basic form. Therefore, a fuzzy logic–based controller has been investigated for potential application in modelling driver. Using some particular and limited number of information from characteristics of human driving operation, the model aims to provide any flexible vehicle path reliably. It generates the vehicle’s trajectory through a number of specified points through which the vehicle must pass. The controller was modified to account for peripheral vision characteristic of human eye, as an input. The simulation is carried out in the MATLAB© programming environment using a Simulink© vehicle model. Both longitudinal and lateral controls were applied in the study. This article adds novel approaches to the limited existing published work on driver steering model using fuzzy logic.

Highlights

Computer simulations have been an important part of the vehicle dynamics design process and the development/improvement of electronic control systems for decades
A control response of a driver model coordinated with visual stimuli and related to the vehicle dynamics control model can potentially make a correct simulation of the vehicle motion possible.[1]
From the driver modelling point of view, there is a general consensus that control occurs at two levels:[2] preview control, in which the driver anticipates the path ahead and makes an appropriate steering action based on knowledge of the vehicle dynamics, and compensatory control, where the driver compensates for errors in the preview control and for disturbances

Summary

Introduction

Computer simulations have been an important part of the vehicle dynamics design process and the development/improvement of electronic control systems for decades. Keywords Vehicle handling dynamics, fuzzy control, driver model, preview control, peripheral vision

Results

Conclusion