Vehicle supervision by bilinear parity equations

Abstract

An approach for supervision of vehicle dynamics is presented which can be used for intelligent vehicle control and state monitoring. In particular, the task is to determine automatically an altered road surface for vehicles (may be due to weather conditions) with possibly lower adhesion between tires and road. Fault detection methods like the parity space approach, which is here presented for a bilinear system, can be used to detect changes in technical processes. These changes indicate different process behaviour in a new operation range. This may be of special importance when the new behaviour is more dangerous for the driver and the passengers of a car. In a further step, suitable classification algorithms were used to detect the actual driving state by processing the residual output.

Fault Detection Based on Parity Equations in Multiple Lane Road Car-Following Models Using Bayesian Lane Change Estimation

“…In this regard, the design of parity equations and the isolation of faults should take into account possible system-specific additive and multiplicative faults [35]. The supervision of vehicle dynamics provided in [36] was a good example related to ITS; the fault detection algorithm described in that paper used bilinear parity relations to determine the alteration state of road surfaces, which is important in intelligent vehicle control and driving state monitoring.…”