Embedded and probabilistic health management for the GPS of autonomous vehicles

The aim of this paper is to propose a complementary Health Management module to monitor the GPS accuracy for autonomous vehicles. Based on sensor information, the error causes of GPS can be observed in some specific contexts (urban, climate...). The proposed module relies on a Bayesian Network model that allows to reinforce the belief of GPS failure based on evidence. A hardware/software implementation of the Health Management module is also proposed for real-time and on-line purposes on an embedded platform.