  This paper surveys a number of recent developments in modern Global
Navigation Satellite Systems (GNSS) and investigates the possible impact on
autonomous driving architectures. Modern GNSS now consist of four independent
global satellite constellations delivering modernized signals at multiple civil
frequencies. New ground monitoring infrastructure, mathematical models, and
internet services correct for errors in the GNSS signals at continent scale.
Mass-market automotive-grade receiver chipsets are available at low Cost, Size,
Weight, and Power (CSWaP). The result is that GNSS in 2020 delivers better than
lane-level accurate localization with 99.99999% integrity guarantees at over
95% availability. In autonomous driving, SAE Level 2 partially autonomous
vehicles are now available to consumers, capable of autonomously following
lanes and performing basic maneuvers under human supervision. Furthermore, the
first pilot programs of SAE Level 4 driverless vehicles are being demonstrated
on public roads. However, autonomous driving is not a solved problem. GNSS can
help. Specifically, incorporating high-integrity GNSS lane determination into
vision-based architectures can unlock lane-level maneuvers and provide
oversight to guarantee safety. Incorporating precision GNSS into LiDAR-based
systems can unlock robustness and additional fallbacks for safety and utility.
Lastly, GNSS provides interoperability through consistent timing and reference
frames for future V2X scenarios.
