Proximity-Event Quantification for Navigating Automated Vehicles in Concurrent Traffic

Tristan Martello, Jason H. Rife, Hadi Wassaf

Peer Reviewed

Abstract: This paper models the frequency at which high-accuracy positioning is needed for safe roadway operations, specifically for automated vehicles navigating in adjacent lanes and traveling in the same direction. One of the significant challenges in defining navigation integrity concepts for ground transportation is in relating a system-safety criterion (e.g., a maximum accident probability per mile driven) to the error distribution for a specific navigation sensor. To address this unsolved problem, this paper develops models to relate navigation events (when the navigation system is stressed) to miles driven. In our modeling, we focus on free-flowing traffic in concurrent, adjacent lanes, where the events that pose significant safety risk occur when one vehicle overtakes another. Using a probabilistic approach, we develop analytic and computational models to estimate the number of such events per mile of vehicle travel, under various operating conditions. As an example, we estimate the rate of passing events in two lanes of concurrent traffic for a representative roadway (Route 16 in Cambridge, MA) as ranging between 0 and 6 events/mile, depending on the time of day.
Published in: Proceedings of the 2024 International Technical Meeting of The Institute of Navigation
January 23 - 25, 2024
Hyatt Regency Long Beach
Long Beach, California
Pages: 186 - 199
Cite this article: Martello, Tristan, Rife, Jason H., Wassaf, Hadi, "Proximity-Event Quantification for Navigating Automated Vehicles in Concurrent Traffic," Proceedings of the 2024 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2024, pp. 186-199. https://doi.org/10.33012/2024.19515
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In