Next-generation traffic signals for Safe, Efficient and Green Intersections

Overview

There is a full PhD scholarship available in the School of Civil and Environmental Engineering at Queensland University of Technology (QUT) to support the newly awarded ARC Linkage Project on Next-generation traffic signals using artificial intelligence-based video analytics for safe, efficient and green intersections. The stipend has a cash value of $32,500 per annum for 3 years.

To apply for this position, please submit the following documents via email to m1.haque@qut.edu.au:

• a detailed curriculum vitae (CV) highlighting academic achievements, research experience and any publications
• academic transcripts from previous degrees
• a cover letter outlining your research interests and motivation for this position.

Research activities

Funded by the prestigious and highly competitive Australian Research Council (ARC) Linkage project scheme, this project aims unify safety, traffic flow efficiency and emissions in real-time that can seamlessly integrate and fundamentally transform the design of traffic signals for safe, efficient and green intersections. In particular, this project will develop a new traffic signal system can better optimise operations, safety and sustainability through proactive and expedient detection of crash precursor conditions applying video analytics and traffic conflict techniques. Utilising the real-time video processing of road user movements, this research develops a machine learning-based intersection safety assessment system that can analyse and assess risk at a transport facility in real-time, make short-term safety forecasts based on current traffic trends and subsequently embed them in a traffic signal system.

Outcomes

A hybrid framework machine learning and econometric models to estimate crash risk, and a bi-level optimisation algorithm will be developed to optimise safety and efficiency. The capability of managing risk in real-time will lead to better flow optimisation, maximising throughputs, and reducing delays and vehicle emissions, resulting in safer, more efficient, and greener intersections.

Skills and experience

• A  master's degree or equivalent in civil or transport engineering
• Strong background in statistical analysis and mathematical programming
• Critical thinking and problem-solving abilities
• Proficiency in technical writing and strong communication skills.

Scholarships

You may be eligible to apply for a research scholarship.

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Keywords

• Transport Safety
• Traffic conflict technique
• Traffic signal design
• Econometric model
• Optimisation

Contact

Contact the supervisor for more information.