Fault-Free Integrity and Continuity for Driverless Urban Vehicle Navigation with Multi-Sensor Integration: A Case Study in Downtown Chicago

Abstract

Driverless vehicles must operate with a safety integrity level, but urban environments degrade GNSS navigation accuracy and thereby fault-free integrity. Integration with INS helps maintain continuity, but position errors drift over time without GNSS signals. Whether modern navigation systems can provide satisfactory integrity for driverless vehicles throughout a city is still undetermined. This research investigates how GNSS and INS, when appropriately augmented by LiDAR ranging from local landmarks, can safely navigate vehicles through a real-world urban environment. We begin by defining safety requirements for driverless vehicles under fault-free conditions and developing measurement models for multi-sensor integrated navigation systems using an EKF. The critical elements of urban navigation are then discussed, including individual INS noise parameter specifications and the effect of velocity updates. Simulations along a nine-kilometer-long urban transect in downtown Chicago show that velocity updates can extend navigation continuity by bridging intermittent GNSS signal availability. However, position reference updates at 35-meter intervals, in our case LiDAR ranges from local landmarks, are needed to achieve 100% navigation availability through the transect.