Classifying other agents’ intentions is a very complex task but it can be very essential in assisting (autonomous or human) agents in navigating safely in dynamic and possibly hostile environments. This paper introduces a classification approach based on support vector machines and Bayesian filtering (SVM-BF). It then applies it to a road intersection problem to assist a vehicle in detecting the intention of an approaching suspicious vehicle. The SVM-BF approach achieved very promising results.


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    Title :

    Using Support Vector Machines and Bayesian Filtering for Classifying Agent Intentions at Road Intersections


    Contributors:

    Publication date :

    2009


    Type of media :

    Report


    Type of material :

    Electronic Resource


    Language :

    English




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