The paper presents a data-driven framework and related field studies on the use of supervised machine learning and smartphone technology for the spatial condition-assessment mapping of roadway pavement surface anomalies. The study explores the use of data, collected by sensors from a smartphone and a vehicle’s onboard diagnostic device while the vehicle is in movement, for the detection of roadway anomalies. The research proposes a low-cost and automated method to obtain up-to-date information on roadway pavement surface anomalies with the use of smartphone technology, artificial neural networks, robust regression analysis, and supervised machine learning algorithms for multiclass problems. The technology for the suggested system is readily available and accurate and can be utilized in pavement monitoring systems and geographical information system applications. Further, the proposed methodology has been field-tested, exhibiting accuracy levels higher than 90%, and it is currently expanded to include larger datasets and a bigger number of common roadway pavement surface defect types. The proposed system is of practical importance since it provides continuous information on roadway pavement surface conditions, which can be valuable for pavement engineers and public safety.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Spatial Roadway Condition-Assessment Mapping Utilizing Smartphones and Machine Learning Algorithms


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    04.04.2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Roadway condition predictive models

    CASTELLI VITTORIO / FRANZ MARTIN / KUNDU GOURAB et al. | Europäisches Patentamt | 2021

    Freier Zugriff

    ROADWAY CONDITION PREDICTIVE MODELS

    CASTELLI VITTORIO / FRANZ MARTIN / KUNDU GOURAB et al. | Europäisches Patentamt | 2018

    Freier Zugriff

    CONDITION BASED ROADWAY ASSISTANCE

    DHOOT AKASH U / PERUMALLA SARASWATHI SAILAJA / RAKSHIT SARBAJIT K | Europäisches Patentamt | 2024

    Freier Zugriff

    Lane-Level Vehicular Localization Utilizing Smartphones

    Zhu, Siyu / Wang, Xiong / Zhang, Zhehui et al. | IEEE | 2016


    Tire-road friction estimation utilizing smartphones

    Jaynes, Michael / Dantu, Ram | IEEE | 2014