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Real-time Analytics on Urban Trajectory Data for Road Traffic Management (2019–2023)

Abstract:
This project aims to develop advanced data management and predictive analytics capabilities to enable road operators and traffic managers to apply insights from multi-modal mobility data to inform decision making in transport network management. Traditional traffic data collected from fixed sensors provide a limited view of network traffic and are unable to capture how a small disruption in traffic movements may ripple through the whole network. This project will demonstrate how transport operators can leverage emerging urban trajectory data from mobile sensors to obtain a holistic multi-modal view of transport networks, better understand the network-wide impacts of their decisions, and, thus, enable city-wide optimization of network flows.
Grant type:
ARC Linkage Projects
Researchers:

  • Associate Professor Jiwon Kim

    Associate Professor
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
    Associate Professor
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology

  • Dr Mehmet Yildirimoglu

    ARC DECRA
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology

  • Professor Mark Hickman

    Professor & Chair of Transport Eng
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
    Affiliate of Dow Centre for Sustain
    Dow Centre for Sustainable Engineering Innovation
    Faculty of Engineering, Architecture and Information Technology
    Deputy Head of School of Civil Engi
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council