Terrain physical characteristics can have a significant impact on passenger vehicle handling, ride quality, and stability. Here, an algorithm is presented to classify terrain using a single suspension-mounted accelerometer. The algorithm passes a measured acceleration signal through a dynamic vehicle model to estimate the terrain profile, and then extracts spatial frequency components of this estimated profile. A method is introduced to identify and remove terrain impulses from the profile that are caused by ruts and potholes. Finally, a supervised support vector machine is employed to classify profile segments as members of pre-defined classes (such as asphalt, brick, gravel, etc.). The classification algorithm is validated with experimental data collected with a passenger vehicle driving in real-world conditions. The algorithm is shown to classify multiple terrain types with reasonable accuracy at a range of typical automotive speeds. It is also shown that the removal of terrain impulses prior to classification improves classifier performance.


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    Titel :

    Speed-independent vibration-based terrain classification for passenger vehicles


    Beteiligte:
    Ward, Chris C. (Autor:in) / Iagnemma, Karl (Autor:in)

    Erschienen in:

    Vehicle System Dynamics ; 47 , 9 ; 1095-1113


    Erscheinungsdatum :

    2009-09-01


    Format / Umfang :

    19 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Speed-independent vibration-based terrain classification for passenger vehicles

    Ward,C.C. / Iagnemma,K. / Massachusetts Inst.of Technol.,US | Kraftfahrwesen | 2009





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