The Impact of Sensor Faults on Connected Autonomous Vehicle Localization
Shinsaku Kuwada, Mathieu Joerger, Matthew Spenko
Abstract
Connected autonomous vehicles (CAVs) can provide benefits over individual vehicles for precise navigation, especially in GNSS-denied environments. CAV collaboration can enhance estimation accuracy, but the safety of collaborative localization in the presence of undetected sensor faults remains underexplored. This paper introduces an integrity monitoring method for CAV collaborative localization in both centralized and decentralized implementations. Fault models for landmark and relative measurements are described, and the probability of hazardous misleading information, or integrity risk, is derived. Simulation and experimental results for notional two-CAV scenarios indicate that collaborative localization reduces integrity risk and enhances navigation safety.
BibTeX
@inproceedings{icra2025_theimpactofsenso,
title = {The Impact of Sensor Faults on Connected Autonomous Vehicle Localization},
author = {Shinsaku Kuwada and Mathieu Joerger and Matthew Spenko},
booktitle = {ICRA 2025},
year = {2025}
}