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This PhD project is part of an Australian Research Council (ARC) Linkage project titled “Real-time Analytics on Urban Trajectory Data for Road Traffic Management”. The overall aim of this ARC Linkage project is to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traffic demand and network congestion propagation. We seek to develop innovative technologies to use a wide variety of data sources, especially massive trajectories of vehicles moving across the network, to better understand people's travel demands and road usage patterns and thus better manage the transport system.
This PhD project will focus on one of the following objectives:
The successful applicant will work as a team with researchers from UQ Transport Engineering Group within the School of Civil Engineering and UQ Data Science Research Group within the School of Information Technology and Electrical Engineering, as well as industry partners from Queensland Department of Transport and Main Roads (TMR) and Transmax Pty Ltd.
The successful applicant will have flexibility to enroll through either the School of Civil Engineering or the School of Information Technology and Electrical Engineering.
To be eligible, you must meet the entry requirements for a higher degree by research.
To apply for admission and scholarship, follow this link. There is no separate application for scholarship because you will have the opportunity to request scholarship consideration on the application for admission.
Before submitting an application you should:
When you apply, please ensure that under the scholarships and collaborative study section you:
See an example of what you have to do
Learn more about applying for a higher degree by research at UQ
Applications will be judged on a competitive basis taking into account the applicant’s previous academic record, publication record, honours and awards, and employment history.
The applicant will demonstrate academic achievement in the field/s of transportation engineering, computer science, applied mathematics and statistics or a closely related area and the potential for scholastic success.
A background or knowledge of machine learning, data science, and programming is highly desirable.
Scholarship value : $28,092 per annum tax-free (2020 rate), indexed annually. A top-up of $5,000 per annum will also be offered.
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