Neural networks and fuzzy data fusion. Application to an on-line and real time vehicle detection system

Abstract

In this article we are presenting an on-line and real-time vehicle detection system. This system detects vehicles passing over magnetic sensors. It works independently of their initial position and of strong magnetic disturbance possibly induced by the load carried on the vehicles. This system is based on the co-operation of reflective agents, using a reliability measure of their outputs. The fusion of the data delivered by each agent is obtained through fuzzy logic rules. The system is also strengthened to resist substantial magnetic disturbance (even non-periodic ones), it uses the three components of the magnetic field, and is rotation-invariant. Furthermore, its modular design opens up many possibilities of evolution.