Awareness to a vehicle's surrounding is necessary for safe driving. Current surround technologies focus on the detection of obstacles in hard-to-view places but may neglect temporal information. This paper seeks the causes of dangerous situations by examining surround behavior. A general hierarchical learning framework is introduced to automatically learn surround behaviors. By observing motion trajectories during natural driving, models of rear vehicle behaviors are obtained in an unsupervised fashion. The extracted behaviors are shown to correspond to typical driving scenarios, vehicle overtake and surround overtake, demonstrating the effectiveness of the learning framework.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Unsupervised learning of motion patterns of rear surrounding vehicles


    Beteiligte:
    Morris, Brendan (Autor:in) / Trivedi, Mohan (Autor:in)


    Erscheinungsdatum :

    01.11.2009


    Format / Umfang :

    3496641 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Unsupervised Clustering of Highway Motion Patterns *

    Tkachenko, Pavlo / Zhou, Jinwei / del Re, Luigi | IEEE | 2019



    Rear lamp for vehicles

    MARCORI FRANCO / RAINIS PIETRO | Europäisches Patentamt | 2015

    Freier Zugriff

    REAR FRAME FOR VEHICLES

    KIM WOO RAM / LEE SANG LAE | Europäisches Patentamt | 2018

    Freier Zugriff

    THE MULTILAYER PERCEPTRON APPROACH TO LATERAL MOTION PREDICTION OF SURROUNDING VEHICLES FOR AUTONOMOUS VEHICLES

    Yoon, Seungje / Kum, Dongsuk | British Library Conference Proceedings | 2016