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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    Title :

    Ontology-based decision making on uncontrolled intersections and narrow roads


    Contributors:


    Publication date :

    2015-06-01


    Size :

    1051423 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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