A Hybrid Method in Driver and Multisensor Data Fusion, Using a Fuzzy Logic Supervisor for Vehicle Intelligence

Abstract

Driving is a very complex task which, at its core, involves the interaction between the driver and his/her environment. It is therefore extremely important to develop driver assistance systems that are centered on the driver. In this regards, various state of the art methods such as multi data sensor fusion techniques are applied on various types of physical sensors such as 3D cameras, ultrasounds, sonar and infrared. However, sensor data alone are always uncertain to some extent due to noise and possible sensor failures. Also the driver, alone, is uncertain because of several parameters such as tiredness and drowsiness. In this paper we show the importance of providing a novel hybrid data fusion algorithm using both physical sensors and the driver's senses, as a supplementary data fusion system while driving. In this article, we use a fuzzy logic controller to manage and fuse the gathered data so take better action than individual driver or sensor fusion.