IMU, INTEGRATED MONITORING UNIT OF THE SAVE DIAGNOSTIC SYSTEM

Abstract In this paper, the diagnostic part of the SAVE system is described. It is composed of three main diagnostic subsystems 1) behavioural diagnosis, 2) physical diagnosis and 3) critical diagnosis. Each subsystem uses different sensors on-board the vehicle and the information is placed in a hierarchical order and mixed to obtain a general diagnosis. A model (black-box), learned off line, is compared on line to the actual driver's performance. Owing to the inherent difficulty of this problem, the model is created by using Statistical and Artificial Intelligence algorithms (Neural Networks and Fuzzy Logic). Laboratory experiments were made and yielded a success rate in excess of 95%. On-line experiments have started using the SAVE demonstrators in which the system is able to differentiate between the driving behaviour of two persons with a success rate of 98% under the same real traffic conditions.