In this paper, we proposed a novel technique to realize accurate and robust position and pose estimation in a dense urban area. The technique make the best use of averaging effect to optimize long time (over several tens of seconds) series sensor data. Our proposed scheme uses just a low-cost GNSS receiver, a MEMS IMU, and a speed sensor. Evaluation tests in a Japanese urban area showed that our proposed scheme can realize robust lane-level absolute positioning results (2DRMS, 0.9 m). In addition, the standard deviation of the heading is 0.4°, and that of the pitch angle is 0.6°. Evaluation tests showed that the accuracy of our proposed scheme almost reached levels of the survey level mapping system, which is equipped with high-cost sensors. On the other hands, the total sensor cost for our prototype was only several hundreds of dollars. We believe that our proposed position and pose estimation scheme enables enhanced vehicle application to systems such as driver assistance systems, autonomous vehicle, and mapping systems.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Low-cost Lane-level Positioning in Urban Area Using Optimized Long Time Series GNSS and IMU Data


    Beteiligte:
    Meguro, Junichi (Autor:in) / Arakawa, Takuya (Autor:in) / Mizutani, Syunsuke (Autor:in) / Takanose, Aoki (Autor:in)


    Erscheinungsdatum :

    01.11.2018


    Format / Umfang :

    2480901 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Vehicular Lane-Level Positioning using Low-Cost Map-Aided GNSS/MEMS IMU Sensors Integration

    Atia, Mohamed M. / Hilal, Allaa | British Library Conference Proceedings | 2018


    Eagleye: A Lane-Level Localization Using Low-Cost GNSS/IMU

    Takanose, Aoki / Kitsukawa, Yuki / Megruo, Junichi et al. | IEEE | 2021


    LaIF: A Lane-Level Self-Positioning Scheme for Vehicles in GNSS-Denied Environments

    Rabiee, Ramtin / Zhong, Xionghu / Yan, Yongsheng et al. | IEEE | 2019


    Real-Time Graph-Based Optimization for GNSS-Doppler Integrated RTK-GNSS/IMU/DR Positioning System in Urban Area

    Takanose, Aoki / Takeuchi, Eijiro / Carballo, Alexander et al. | IEEE | 2023


    Lane level positioning using particle filtering

    Selloum, A. / Betaille, D. / Le Carpentier, E. et al. | IEEE | 2009