This paper addresses collective perception for connected and automated driving. It proposes the adaptation of filtering rules based on the currently available channel resources, referred to as Enhanced DCC-Aware Filtering (EDAF).


    Access

    Download


    Export, share and cite



    Title :

    Congestion Aware Objects Filtering for Collective Perception


    Contributors:


    Publication date :

    2021


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Congestion Aware Objects Filtering for Collective Perception

    Delooz, Quentin / Festag, Andreas / Vinel, Alexey | DataCite | 2021


    Design and Performance of Congestion-Aware Collective Perception

    Delooz, Quentin / Riebl, Raphael / Festag, Andreas et al. | IEEE | 2020


    Collective perception and decentralized congestion control in vehicular ad-hoc networks

    Gunther, Hendrik-Jorn / Riebl, Raphael / Wolf, Lars et al. | IEEE | 2016


    Environment-aware Optimization of Track-to-Track Fusion for Collective Perception

    Volk, Georg / Gamerdinger, Jorg / von Bernuth, Alexander et al. | IEEE | 2022


    Simulation-based Performance Optimization of V2X Collective Perception by Adaptive Object Filtering

    Delooz, Quentin / Festag, Andreas / Vinel, Alexey et al. | IEEE | 2023