Traffic congestion is an inherent and hard issue to be tackled in huge urban areas, particularly in developing countries where transportation infrastructures have not been grown well to fulfill speedy developing request demands. This paper proposes novel solutions to these issues by devising mobile crowd-sourcing based approaches to traffic estimation. A framework for effective collecting, integrating and analyzing traffic-related data shared by mobile crowds has been devised. Besides, essential issues on predicting traffic conditions at streets where real-time data is missed are also resolved by applying data mining techniques to historical data. A prototype system has been developed to validate the proposed solutions. The experimental results show the feasibility and the effectiveness of the proposed methods revealing that they are ready to be applied in the practice.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    CROWD SOURCED TRAFFIC REPORTING

    GUEZIEC ANDRE | European Patent Office | 2017

    Free access

    CROWD SOURCED TRAFFIC REPORTING

    GUEZIEC ANDRE | European Patent Office | 2018

    Free access


    CROWD SOURCED TRAFFIC AND VEHICLE MONITORING SYSTEM

    EAKINS HARRY | European Patent Office | 2022

    Free access

    Using crowd-sourced traffic data and open-source tools for urban congestion analysis

    Khaula Alkaabi / Mohsin Raza / Esra Qasemi et al. | DOAJ | 2024

    Free access