In this article, autonomous ground vehicle (AGV) path planning is considered. The AGV is assumed to be equipped with receivers capable of producing pseudorange measurements to overhead global navigation satellite systems (GNSS) satellites and to cellular base stations in its environment. Parameters of the cellular pseudoranges related to the transmitter clock bias are estimated in an initialization step in an open-sky environment. The AGV fuses these pseudoranges to produce an estimate about its own states. The AGV is also equipped with a three-dimensional building map of the environment. Starting from a known starting point, the AGV desires to reach a known target point by taking the shortest distance, while minimizing the AGV's position estimation error and guaranteeing that the AGV's position estimation uncertainty is below a desired threshold. Toward this objective, a so-called signal reliability map is first generated, which provides information about regions where large errors due to poor GNSS line-of-sight or cellular signal multipath are expected. The vehicle uses the signal reliability map to calculate the position mean-squared error (MSE). An analytical expression for the AGV's state estimates is derived, which is used to find an upper bound on the position bias due to multipath. An optimal path planning generation approach, which is based on Dijkstra's algorithm, is developed to optimize the AGV's path while minimizing the path length and position MSE, subject to keeping the position estimation uncertainty and position estimation bias due to multipath below desired thresholds. The path planning approach yields the optimal path together with a list of feasible paths and reliable GNSS satellites and cellular base stations to use along these paths.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Autonomous Ground Vehicle Path Planning in Urban Environments Using GNSS and Cellular Signals Reliability Maps: Models and Algorithms


    Beteiligte:
    Ragothaman, Sonya (Autor:in) / Maaref, Mahdi (Autor:in) / Kassas, Zaher M. (Autor:in)


    Erscheinungsdatum :

    01.06.2021


    Format / Umfang :

    3405002 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    INTEGRITY-BASED PATH PLANNING STRATEGY FOR URBAN AUTONOMOUS VEHICULAR NAVIGATION USING GPS AND CELLULAR SIGNALS

    Lee, Halim / Seo, Jiwon / Kassas, Zaher M. | British Library Conference Proceedings | 2020


    Path Planning for Autonomous Bus Driving in Urban Environments

    Oliveira, Rui / Lima, Pedro F. / Pereira, Gonçalo Collares et al. | ArXiv | 2019

    Freier Zugriff


    PATH PLANNING IN AUTONOMOUS DRIVING ENVIRONMENTS

    GYLLENHAMMAR MAGNUS / SIVENCRONA HÅKAN | Europäisches Patentamt | 2024

    Freier Zugriff