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• W3208055211 abstract "Cooperative Perception is an emergent technology that profits from the exchanged perception information between vehicles. However, the inconsistency resulting from the reuse of the same information is a main issue that arises. In this paper, we focus on the study of the Split Covariance Intersection Filter (SCIF), a method capable of handling both independent and arbitrarily correlated estimates and observation errors. We are interested in its use in a Cooperative Perception application to incorporate information coming from other vehicles, which may or may not have been tracked, in a generic tracking solution. A simple case study is first presented to build a deep understanding of the filter tuning, then real experiments carried out with three vehicles equipped with GNSS, camera, LiDAR and High Definition (HD) map features are reported to study how a full tracking architecture relying on SCIF behaves in a real-world situation." @default.
• W3208055211 created "2021-11-08" @default.
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• W3208055211 date "2021-09-19" @default.
• W3208055211 modified "2023-10-11" @default.
• W3208055211 title "Data Fusion with Split Covariance Intersection for Cooperative Perception" @default.
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• W3208055211 doi "https://doi.org/10.1109/itsc48978.2021.9564963" @default.
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