Many Advanced Driver Assistance Systems (ADAS) have been developed to improve car safety. However, it is still a challenging problem to make autonomous vehicles to drive safely on urban streets such as uncontrolled intersections (without traffic lights) and narrow roads. In this paper, we introduce a decision making system that can assist autonomous vehicles at uncontrolled intersections and narrow roads. We constructed a machine understandable ontology-based Knowledge Base, which contains maps and traffic regulations. The system makes decisions in comply with traffic regulations such as Right-Of-Way rules when it receives a collision warning signal. The decisions are sent to a path planning system to change the route or stop to avoid collisions.


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    Titel :

    Ontology-based decision making on uncontrolled intersections and narrow roads


    Beteiligte:
    Zhao, Lihua (Autor:in) / Ichise, Ryutaro (Autor:in) / Yoshikawa, Tatsuya (Autor:in) / Naito, Takeshi (Autor:in) / Kakinami, Toshiaki (Autor:in) / Sasaki, Yutaka (Autor:in)


    Erscheinungsdatum :

    01.06.2015


    Format / Umfang :

    1051423 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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