As autonomous vehicles operating on the urban roads, being conscious of the road context is a crucial prerequisite to safely negotiate with the other vehicles. This paper proposes a probabilistic approach to infer the road context from the vehicle behaviors. Specifically, the consistencies of the randomly-observed vehicle states are extracted first, thereafter the road context is inferred in a probabilistic manner by coupling these consistencies. The feasibility of the proposed road context inference approach has been validated by the case study of an urban road that includes roundabout and T-junction. The experiments demonstrate that the inferred road context can be successfully applied for the autonomous vehicles in various aspects.


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    Title :

    Probabilistic road context inference for autonomous vehicles


    Contributors:
    Wei Liu, (author) / Seong-Woo Kim, (author) / Ang, Marcelo H. (author)


    Publication date :

    2015-05-01


    Size :

    2637702 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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