Model of an Intelligent Automobile Driving Assistance System

Abstract

The recent times with the evolution of computing has seen the emergence of intelligent control as a major tool in vehicles for improving system efficiency. With newer technologies one no longer solely rely on the mechanical designs and with the availability of advanced vehicular technologies such as cruise control, antilock braking etc which reduced the dependence of human maneuverability skills. The present work proposes a solution on automotive drive technology where the system response would be equally smooth irrespective of the driver’s skill. The vehicles available in the market respond best only to those who have near perfect driving skills, which unfortunately a majority of new drivers lack in. Besides one don’t have enough time to learn driving, instead choose to learn with time. On the other hand, vehicles presently are coming with super sensitive clutch and accelerators same as it would have been in a racing car and this worsens the learning process. Except for those who know how to handle such technologies, a majority of new drivers encounter common problems such as sudden engine stoppage due to the unsynchronized rate in which the clutch is released and the accelerator is pressed, apart from this sudden acceleration due to super sensitive technology and over revving of the engine. Besides this there is a constant fear of the vehicle coming to a sudden halt when it is running at lower speeds but a comparatively higher gear ratio, which mainly is due to a sudden de-acceleration of the vehicle & to keep the engine running needs some skills in changing the gears, which we learn with time. It is the vehicle which actually suffers from this imbalance on the long run leading to reduction in engine efficiency. When the variables/number of drivers per vehicle increases the problem worsens as each variable has his own driving skills. This paper proposes a model of drive assistance system which would be designed to hide the discrepancies of the driver by using fuzzy rule base systems which would measure the rate of change of variables such as acceleration, clutch as well as brake and gear shift.