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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    Titel :

    Data fusion considering 'negative' information for cooperative vehicles


    Weitere Titelangaben:

    Datenzusammenführung unter Berücksichtigung von 'Negativinformationen' für teilnehmende Fahrzeuge


    Beteiligte:
    Tischler, Karin (Autor:in) / Vogt, Heike S. (Autor:in)


    Erscheinungsdatum :

    2007


    Format / Umfang :

    5 Seiten, 3 Bilder, 4 Tabellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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