The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.


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    Title :

    Optimization for Shared-Autonomy in Automotive Swarm Environment


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE World Congress & Exhibition ; 2009



    Publication date :

    2009-04-20




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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