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Data Fusion considering ‘Negative’ Information for Cooperative Vehicles

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2007

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Gesellschaft für Informatik e. V.

Zusammenfassung

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.

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Tischler, Karin; Vogt, Heike S. (2007): Data Fusion considering ‘Negative’ Information for Cooperative Vehicles. Informatik 2007 – Informatik trifft Logistik – Band 2. Bonn: Gesellschaft für Informatik e. V.. PISSN: 1617-5468. ISBN: 978-3-88579-206-1. pp. 150-154. Regular Research Papers. Bremen. 24.-27. September 2007

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