Fault Tolerant Consensus for Vehicle State Estimation: A Cyber-Physical Approach

Abstract

A novel cyber physical method is proposed and experimentally verified for reliable distributed estimation of vehicle longitudinal velocity, robustly to road friction condition variations. In this method, the vehicle speed estimated at each of the four corners of the vehicle, using a linear parameter-varying observer in the physical layer, and speed data measured by a conventional low-cost GPS are incorporated in a distributed structure (in the cyber layer) to enhance the reliability of the estimate. The method minimizes a cost function quantizing the effect of disturbances on each corner's estimation and adversaries due to occasional GPS signal drops. A fault-tolerant estimation policy is integrated to deal with large deviations in corner estimations, which have unexpectedly high levels of confidence. The main advantages of the proposed method are increased reliability on various road surface conditions and robustness to faults, as confirmed by road tests. Several experimental tests, including lane change and low-excitation maneuvers, with various powertrain configurations on dry and slippery roads demonstrate the efficiency of the algorithm.