Negative information provides important additional knowledge that is not exploited for sensor data fusion tasks by default. This paper presents a new approach to incorporate such information about unoccupied, observed areas or missing measurements in the Kalman filtering process. For this purpose, a combination with a grid-based method is proposed to generate a visibility map. This enables a plausibility check and an enhanced understanding for the collaborative perception of the environment with multiple cognitive vehicles. Results from a realistic traffic simulation are presented.
Data fusion considering 'negative' information for cooperative vehicles
Datenzusammenführung unter Berücksichtigung von 'Negativinformationen' für teilnehmende Fahrzeuge
Informatik trifft Logistik, INFORMATIK, Jahrestagung der Gesellschaft für Informatik e.V., 37 ; 150-154
2007
5 Seiten, 3 Bilder, 4 Tabellen
Conference paper
English
Information fusion for cooperative vehicles
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