Environment models are necessary for autonomous driving. The distinction between drivable and non-drivable underground is elementary. This paper presents adaptions for radar based occupancy gridmaps, which are a common representation of the environment. In contrast to standard occupancy gridmaps or in general standard inverse radar sensor models, our approach works with velocity dependent parameters and extends free space calculations. Consequently, the map quality varies less and the information content of the ego vehicle's immediate vicinity is higher. Experiments with ground truth data show that the proposed algorithm produces accurate environment models in urban scenes.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Adaptions for Automotive Radar Based Occupancy Gridmaps


    Contributors:


    Publication date :

    2018-04-01


    Size :

    5536012 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Advances in controls and adaptions for disabled drivers

    Wood,N.T.A. / Low Cost Automation Centre,Univ.of Birmingham,GB | Automotive engineering | 1987


    Semantic Segmentation-Based Occupancy Grid Map Learning With Automotive Radar Raw Data

    Jin, Yi / Hoffmann, Marcel / Deligiannis, Anastasios et al. | IEEE | 2024


    Automotive occupancy sensor (AOS)

    Moloney, J. / Corrado, A. / Peteuil, G. et al. | British Library Conference Proceedings | 1998


    Occupancy Radar Grid

    Jakob, Lombacher / Laudt, Kilian / Hahn, Markus et al. | British Library Conference Proceedings | 2017


    Radar-based occupancy detector for automobiles

    SCHEELE JUERGEN / FESSHAIE EFREM / MISEVI{HACEK OVER (C)}IUS RIMANTAS | European Patent Office | 2022

    Free access