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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

  • 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
Funded by:
Australian Research Council