The advent of Big Data has triggered disruptive changes in many fields including Intelligent Transportation Systems (ITS). The emerging connected technologies created around ubiquitous digital devices have opened unique opportunities to enhance the performance of the ITS. However, magnitude and heterogeneity of the Big Data are beyond the capabilities of the existing approaches in ITS. Therefore, there is a crucial need to develop new tools and systems to keep pace with the Big Data proliferation. In this paper, we propose a comprehensive and flexible architecture based on distributed computing platform for real-time traffic control. The architecture is based on systematic analysis of the requirements of the existing traffic control systems. In it, the Big Data analytics engine informs the control logic. We have partly realized the architecture in a prototype platform that employs Kafka, a state-of-the-art Big Data tool for building data pipelines and stream processing. We demonstrate our approach on a case study of controlling the opening and closing of a freeway hard shoulder lane in microscopic traffic simulation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Big data analytics architecture for real-time traffic control


    Contributors:


    Publication date :

    2017-06-01


    Size :

    433598 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Real-time video analytics for traffic conflict detection and quantification

    YANG JIDONG J | European Patent Office | 2019

    Free access

    REAL-TIME VIDEO ANALYTICS FOR TRAFFIC CONFLICT DETECTION AND QUANTIFICATION

    YANG JIDONG J | European Patent Office | 2018

    Free access

    Real-time predictive analytics to estimate air traffic flow rates

    Kelly, Carol / Craig, Keith / Matthews, Michael | IEEE | 2015


    REAL TIME STREAMING ANALYTICS FOR FLIGHT DATA PROCESSING

    SEEMA CHOPRA / SUDHEER PALYAM / JAMES SCHIMERT et al. | European Patent Office | 2019

    Free access

    Reconstructing fixed time traffic light cycles by camera data analytics

    Schonfelder, Marco / Protschky, Valentin / Back, Thomas | IEEE | 2017