Multi-Objective Genetic Algorithm (MOGA) Optimisation for Network Widening and Maintenance Scheduling (Main Roads WA, 2019/20)

The objective of the project is to incorporate the use of MOGA to optimise locality and timing of integrated works between road widening and maintenance. Specifically, outcomes of the MOGA will minimise costs by integrating work while improving road user experience and safety by targeting the highest benefit roads. Numerous...

Drone video analytics (Main Roads WA, 2019/20)

The objectives of this project are to explore new techniques for automated camera calibration and undertake video analytics from drone footage at signalised intersections and roundabouts. Automated camera calibration is necessary to make the system operational. The feasibility of a few new techniques will be explored. Video analytics of signalised...

Managing transport system investment risk: enhancing patronage predictions and adapting strategic asset management and appraisal processes to account for emerging trends and uncertainty (iMOVE CRC-PATREC, 2019-2020)

Governments are responsible for ensuring public funds are invested wisely for the benefit of society. For transport planners and government transport agencies, the uncertainties of emerging technologies and changing trends challenge conventional transportation decision-making, both for long- and short-term planning. The purpose of this project is to adapt key existing...

Planning intermodal and general logistics infrastructure for the future needs of Perth (iMOVE CRC-PATREC, 2018-2019)

This project consists of a suite of related research streams to support the state of WA and the WestPort Taskforce in long term planning for landside logistics infrastructure and services to support container trade growth. Studies include analysis of aspects of intermodal systems in order to maximise the future use...

Enhanced short and longer term network performance prediction capabilities through data-driven analytics and simulation (iMOVE CRC-PATREC, 2018-2019)

This project aims to improve the ability of road authorities to predict network performance in the short term using data-driven analytics and to incorporate the impact of Automated Vehicles (AVs) in longer term predictions. The project has two subprojects: Subproject 1:  Develop mathematical and data-driven empirical models (mathematical prediction using...