Vehicle sensor and actuator fault detection algorithm for automated vehicles

This paper presents a vehicle sensor and actuator fault detection algorithm for automated vehicles. The diagnostic system is designed to monitor steering wheel angle, yaw-rate, and wheel speed sensors and steering, throttle, and brake actuators used by the lateral and longitudinal controllers of the vehicle. Different combinations of the observer estimates, the sensor measurements, and the control commands are used to construct a bank of residuals. A fault in any of the vehicle sensors and actuators leads to increase of the unique subset of residuals. The adaptive threshold is used to enable exact identification of the abnormal increase of residual. The fault detection performance and its reliability of the proposed algorithm have been investigated via computer simulation studies and real-time vehicle tests. The enhancement of the fault detection allows for realization of autonomous driving vehicle which uses actuation by embedded computer.