Sequential FDIA for Autonomous Integrity Monitoring of Navigation Maps on Board Vehicles

This paper addresses the problem of fault detection, isolation, and adaptation (FDIA) in navigation systems on board passenger vehicles. The aim is to prevent malfunctions in systems such as advanced driving assistance systems and autonomous driving functions that use data provided by the navigation system. The integrity of the estimation of the vehicle position provided by the navigation system is continuously monitored and assessed. The proposed approach uses an additional estimate of vehicle position that is independent of the navigation system and based on data from standard vehicle sensors. First, fault detection consists in comparing the two estimates using a sequential statistical test to detect discrepancies despite the presence of noise. Second, fault isolation and adaptation is introduced to identify faulty estimates and to provide a correction where necessary. The FDIA framework presented here utilizes repeated trips along the same roads as a source of redundancy. Relevant properties of this formalism are given and verified experimentally using an equipped vehicle in rural and urban conditions and with various map faults. Results show that sequential FDIA performed well, even in difficult GNSS conditions.