Simulation tools are frequently used to analyze vehicular networks. However, these tools are not ready yet to model the world in the necessary level of detail for Collective Perception. The network load generated by the Collective Perception Service highly depends on the sender's sensors, which are modeled insufficiently by current vehicular network simulators. This paper presents an Environment Model extension to Artery, a popular simulation framework for the ETSI C-ITS communication stack. It enables sensor-equipped vehicles to perceive objects from their perspective individually to improve the realism of perception. Furthermore, it adds new sensors that produce synthetic object data for detected objects based on the characteristics of various automotive sensors. A performance evaluation shows that the computational overhead for the extension is limited, so it is suitable even for large-scale simulation studies using Artery.


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    Title :

    Towards Improving Realism of Perception in Artery


    Contributors:


    Publication date :

    2023-06-01


    Size :

    1242616 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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