This paper deals with the design of a fault detection and isolation (FDI) system for an intelligent vehicle, a vehicle equipped with\nadvanced driver assistance system (ADAS). The ADASs are outfitted with sensors for acquiring various information about the\nvehicle and its surroundings. Since these sensors are sensitive to faults, an efficient FDI system should be developed. The designed\nFDI system is comprised of three parts: a detection part, a decision part, and a fault management part. The detection part applies\na generalized observer scheme (GOS). In the GOS, there is bank of extended Kalman filters (EKFs), each excited by all except one\nsensor measurement. The residual generated from the measurement update of each EKF is therefore sensitive to all sensor faults\nbut one. This way, the fault sensitivity pattern of the residual makes it possible to detect a fault and locate the faulty sensor. The\ndesigned FDI system has been implemented and tested off-line with actual experiment data. Good results have been obtained with\ndiagnosing individual sensor faults and outputting fault-free vehicle states.
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