Zusammenfassung Automated driving is a key technology for the future of transportation. There are several motivations to develop automated vehicles. First and foremost, it promises to reduce the number of traffic accidents. Figure 1 shows the accidents recorded by the German police over the past years ([1]) ranging back to 1960.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Core components of automated driving – algorithms for situation analysis, decision-making, and trajectory planning


    Beteiligte:
    Lienke, Christian (Autor:in) / Schmidt, Manuel (Autor:in) / Wissing, Christian (Autor:in) / Keller, Martin (Autor:in) / Manna, Carlo (Autor:in) / Nattermann, Till (Autor:in) / Bertram, Torsten (Autor:in)


    Erscheinungsdatum :

    28.11.2019


    Format / Umfang :

    21 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Deutsch




    Core components of automated driving - algorithms for situation analysis, decision-making and trajectory planning

    Lienke, Christian / Schmidt, Manuel / Wissing, Christian et al. | TIBKAT | 2020



    Learning from Demonstration: Situation-Adaptive Lane Change Trajectory Planning for Automated Highway Driving

    Liu, Yulong / Sun, Liting / He, Xiangkun et al. | British Library Conference Proceedings | 2020


    Trajectory planning for high dynamic automated driving

    Keller,T. / Wimmershoff,M. / Hardy,J. et al. | Kraftfahrwesen | 2014


    Model Predictive Trajectory Planning for Automated Driving

    Yi, Boliang / Bender, Philipp / Bonarens, Frank et al. | IEEE | 2019