Planning, acting, and recognizing intentions of participants in traffic situations requires the processing of complex spatio-temporal situations. If spatio-temporal information was represented quantitatively it would result in a huge amount of data. We claim that an abstraction to a qualitative description leads to more stable representations as similar situations at the quantitative level are mapped to one qualitative representation. Our approach is evaluated by emulating traffic situations with settings in the Robocup small-sized league.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Dynamic-preserving qualitative motion description for intelligent vehicles


    Beteiligte:
    Miene, A. (Autor:in) / Lattner, A.D. (Autor:in) / Visser, U. (Autor:in) / Herzog, O. (Autor:in)


    Erscheinungsdatum :

    01.01.2004


    Format / Umfang :

    536899 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    TAP1.21 Dynamic-Preserving Qualitative Motion Description for Intelligent Vehicles

    Miene, A. / Lattner, A. D. / Visser, U. et al. | British Library Conference Proceedings | 2004


    Active safe motion planning for intelligent vehicles in dynamic environments

    Tian, Hongqing / Wang, Jianqiang / Huang, Heye | IEEE | 2021


    Longitudinal Motion Control for Intelligent Vehicles

    Prof. Cheng, Hong | Springer Verlag | 2011


    Privacy-Preserving Dynamic Task Scheduling for Autonomous Vehicles

    Muthurajkumar, S. / Karthikeyan, C. Ajay / Pradeep, K. et al. | Springer Verlag | 2022


    Motion Planning of Intelligent Vehicles: A Survey

    Chen, Yang / He, Hangen / An, Xiangjing | IEEE | 2006