A histogram filter is used to estimate the state of a vehicle traveling along a known road network. Our contribution is to provide a framework to estimate vehicle states without knowing its route or the final destination. The vehicle is constrained to travel on the road network with an unknown but bounded speed. We account for road intersections by applying a likelihood to the possible direction of travel during the prediction step of the filter. These likelihoods are determined by system parameters that model how likely roads will be taken, and the maneuvers that the vehicle will likely perform.


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    Title :

    Vehicle State Estimation within a Road Network using a Bayesian Filter


    Contributors:


    Publication date :

    2011


    Size :

    6 Seiten, 6 Quellen



    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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