This paper introduces a robust prediction- and cost-function based algorithm for autonomous freeway driving. A prediction engine is built so that the autonomous vehicle is able to estimate human drivers' intentions. A cost function library is used to help behavior planners generate the best strategies. Finally, the algorithm is tested in a real-time vehicle simulation platform used by the Tartan Racing Team for the DARPA Urban Challenge 2007.


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    Title :

    A robust autonomous freeway driving algorithm


    Contributors:


    Publication date :

    2009-06-01


    Size :

    1089754 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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