Localization robustness improvement for an autonomous race car using multiple extended Kalman filters

In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one ba...

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Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers. Part D, Journal of automobile engineering Journal of automobile engineering, 2024-07
Main Authors: Enisz, Krisztián, Szalay, István, Horváth, Ernő
Format: Article
Language:English
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Summary:In this paper, we introduce a vehicle localization method designed for the SZEnergy race car, which competes in the Shell Eco-marathon. The proposed method comprises four different extended Kalman filter-based localization algorithms and a selection algorithm that determines the most suitable one based on vehicle speed, GNSS availability, and signal quality. The low-speed Kalman filters are based on a kinematic vehicle model while the high-speed variants are based on a dynamic vehicle model. Several measurements were performed during test maneuvers to evaluate the performance of the filters. The proposed method succesfully handles sensor miscalibration and GNSS outages.
ISSN:0954-4070
2041-2991
DOI:10.1177/09544070241266281