Vehicle sideslip angle, defined as the angle between the longitudinal axis of a vehicle and its velocity vector, is a crucial parameter in vehicle dynamics. Unfortunately vehicle sideslip angle is very hard to access directly, therefore a variety of estimation methods have been developed so far. Such estimation methods are essentially based on model-based approaches or neural networks. This paper looks at the problem from a fresh angle, by investigating possible solutions to measure vehicle sideslip angle via computer vision techniques, harnessing recent improvements in computer vision algorithms. Preliminary experiments on a radio-controlled scaled vehicle show promising results using the "phase correlation" algorithm.


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    Titel :

    Computer vision approaches for vehicle sideslip angle estimation


    Beteiligte:


    Erscheinungsdatum :

    28.06.2023


    Format / Umfang :

    1792591 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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