Automated driving, in general, and platooning, in particular, represent a highly active field of research. The idea to automate traffic is closely related to high expectations in both individual and public transport. However, the complexity of automated driving requires methods beyond the traditional development approaches. This chapter describes a state-of-the-art methodology to organise and systematically address a comprehensive set of research questions in the context of truck platooning. Following best practices, an evaluation design is presented, which ensures the alignment of research efforts with the actual research agenda, that is, to answer the right questions. Specifically, the benefits of automated driving and their conflicting relationships are explored and the entities that affect automated driving performance and their interactions are presented. Finally, a solution concept that adequately addresses the complexity and the stochastic nature of the problem is presented. The solution concept consists of several key methods such as scenario-based design and stochastic simulation, data mining and complexity and robustness management.


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    Titel :

    Research Design and Evaluation Strategies for Automated Driving


    Weitere Titelangaben:

    Lecture Notes in Intelligent Transportation and Infrastructure


    Beteiligte:
    Schirrer, Alexander (Herausgeber:in) / Gratzer, Alexander L. (Herausgeber:in) / Thormann, Sebastian (Herausgeber:in) / Jakubek, Stefan (Herausgeber:in) / Neubauer, Matthias (Herausgeber:in) / Schildorfer, Wolfgang (Herausgeber:in) / Kuhn, Andreas (Autor:in) / Carmona, José (Autor:in) / Thonhofer, Elvira (Autor:in)


    Erscheinungsdatum :

    2022-04-26


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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