This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles


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    Title :

    Machine learning and optimization techniques for automotive cyber-physical systems


    Contributors:

    Publication date :

    2023


    Size :

    xv, 789 Seiten


    Remarks:

    Illustrationen, Diagramme
    Literaturangaben



    Type of media :

    Book


    Type of material :

    Print


    Language :

    English



    Classification :

    DDC:    629.20285631




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