Real-time Analytics on Urban Trajectory Data for Road Traffic Management (2019–2022)

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:
  • ARC DECRA
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
  • Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
  • Lecturer in Transport Engineering
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
  • Professor & Chair of Transport Eng
    School of Civil Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council