A probabilistic system for automatic maneuver recognition is in development at the German Aerospace Center (DLR). Automatic maneuver recognition in the automobile would enable assistance systems to offer relevant, maneuver-specific assistance to the driver. Major obstacles to maneuver recognition in the automobile today are the wide variety of styles in which driving maneuvers are performed and the presence of uncertain and sometimes invalid sensor values, which traditional rule-based systems are ill-equipped to handle. Bayesian models, which offer a solid, theoretical framework for the derivation of inferences from uncertain evidence, are used for the inference of the driving maneuver being performed. Driver behavior analysis and tests of a prototype maneuver-recognition system are performed in real traffic using the DLR ViewCar, a research vehicle equipped with cameras and sensors to measure and record CAN-Bus, environment and driver data. Experiments with the prototype system yield a driving maneuver recognition rate of approximately 92%.


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    Title :

    Automatic maneuver recognition in the automobile: The fusion of uncertain sensor values using Bayesian models


    Additional title:

    Automatisches Manöver-Erkennen durch das Fahrzeug: die Zusammenführung unsicherer Sensormesswerte mit Hilfe des Bayes-Ansatzes


    Contributors:


    Publication date :

    2006


    Size :

    5 Seiten, 2 Bilder, 2 Tabellen, 9 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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