  Predicting the safety of urban roads for navigation via global navigation
satellite systems (GNSS) signals is considered. To ensure safe driving of
automated vehicles, the vehicle must plan its trajectory to avoid navigating on
unsafe roads (e.g., icy conditions, construction zones, narrow streets, etc.).
Such information can be derived from the roads' physical properties, vehicle's
capabilities, and weather conditions. From a GNSS-based navigation perspective,
the reliability of GNSS signals in different locales, which is heavily
dependent on the road layout within the surrounding environment, is crucial to
ensure safe automated driving. An urban road environment surrounded by tall
objects can significantly degrade the accuracy and availability of GNSS
signals. This article proposes an approach to predict the reliability of
GNSS-based navigation to ensure safe urban navigation. Satellite navigation
reliability at a given location and time on a road is determined based on the
probabilistic position error bound of the vehicle-mounted GNSS receiver. A
metric for GNSS reliability for ground vehicles is suggested, and a method to
predict the conservative probabilistic error bound of the GNSS navigation
solution is proposed. A satellite navigation reliability map is generated for
various navigation applications. As a case study, the reliability map is used
in the proposed optimization problem formulation for automated ground vehicle
safety-constrained path planning.
