The latest improvements in automotive technologies are enabling a paradigm shift in transportation systems: shared mobility, electrification, connectivity, and autonomous driving are envisaged as the four major trends in the near future. To support these advancements, advanced control strategies are required for the control of both single vehicles and formations of Connected and Automated Vehicles (CAVs). These, in turn, lead to beneficial features such as greater safety, improved efficiency, and better exploitation of the traffic infrastructure. Autonomously controlled vehicles can exhibit advanced performances which determine an improved safety even in cases where the distances are tight, while the inter-vehicle communication opens a huge number of new possibilities. Among others, unidimensional and bidimensional formations can be employed as dynamic actuators in traffic control. In this Dissertation a discussion about advanced control techniques for multi-agent automotive systems is provided, proposing novel research results. Starting from a brief introduction to the control of single vehicles (in which electric and hybrid vehicles opened a broad range of new possibilities), the discussion is then extended to the robust control of platoons via the exploitation of Sliding Mode Control techniques. Lastly, an extension to the formation control case is examined, presenting a novel iterative method for the creation and dynamic reshape of formations in highway scenarios. ; The latest improvements in automotive technologies are enabling a paradigm shift in transportation systems: shared mobility, electrification, connectivity, and autonomous driving are envisaged as the four major trends in the near future. To support these advancements, advanced control strategies are required for the control of both single vehicles and formations of Connected and Automated Vehicles (CAVs). These, in turn, lead to beneficial features such as greater safety, improved efficiency, and better exploitation of the traffic infrastructure. ...


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    Titel :

    Advanced Control of Multiagent Automotive Systems



    Erscheinungsdatum :

    2021-04-30


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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