Comprehensive perception of the environment is crucial for the safe operation of autonomous vehicles. However, the perception capabilities of autonomous vehicles are limited due to occlusions, limited sensor ranges, or environmental influences. Collective Perception (CP) aims to mitigate these problems by enabling the exchange of information between vehicles. A major challenge in CP is the fusion of the exchanged information. Due to the enormous bandwidth requirement of early fusion approaches and the interchangeability issues of intermediate fusion approaches, only the late fusion of shared detections is practical. Current late fusion approaches neglect valuable information for local detection, this is why we propose a novel fusion method to fuse the detections of cooperative vehicles within the local LiDAR-based detection pipeline. Therefore, we present Collective PV-RCNN (CPV-RCNN), which extends the PV-RCNN++ framework to fuse collective detections. Code is available at https://github.com/ekut-es


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Collective PV-RCNN: A Novel Fusion Technique using Collective Detections for Enhanced Local LiDAR-Based Perception


    Contributors:


    Publication date :

    2023-09-24


    Size :

    349118 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    MR3D-Net: Dynamic Multi-Resolution 3D Sparse Voxel Grid Fusion for LiDAR-Based Collective Perception

    Teufel, Sven / Gamerdinger, Jorg / Volk, Georg et al. | IEEE | 2024


    S-LDM: Server Local Dynamic Map for Vehicular Enhanced Collective Perception

    Raviglione, Francesco / Carletti, Carlos Mateo Risma / Casetti, Claudio et al. | IEEE | 2022


    Object Fusion for Collective Perception: Will it Scale?

    Willecke, Alexander / Stahl, Roman / Wolf, Lars C. | IEEE | 2024


    Situational Collective Perception: Adaptive and Efficient Collective Perception in Future Vehicular Systems

    Khalil, Ahmad / Meuser, Tobias / Alkhalili, Yassin et al. | TIBKAT | 2022

    Free access

    Collective Perception: A Safety Perspective

    Schiegg, Florian A.. / Llatser, Ignacio / Bischoff, Daniel et al. | TIBKAT | 2020

    Free access