Watch the video recording of our webinar discussing the final report of our ‘Innovative local transport: Community transport of the future’ project.
Download the final report from iMOVE’s ‘Innovative local transport: Community transport of the future’ project.
Literature review/stakeholder interviews to guide the estimation of the extent, spatial distribution, & nature of transport disadvantage in the Greater Perth region.
Register for our webinar ‘Delivering community transport that meets the diverse needs of our growing population’, and improve its service and accessibility.
A scoping study to identify opportunities to improve urban freight planning tertiary education in Australia, improving education outcomes for freight logistics.
Our ‘Encouraging continuation of work from home post-pandemic’ project has been completed, and the final report is available here.
This PhD project will develop traffic management strategies and infrastructure allocation algorithms needed to improve emergency vehicle logistics.
This project will create a model for estimating delays at Perth’s traffic signals, which would inform project decisions and operational strategies.
Using state-of-the-art machine learning algorithms, this study will use a novel modelling approach to accurately predict traffic crashes in real-time.
This PhD project will, at its conclusion, demonstrate how the roles and responsibilities of different stakeholders impact building a collaborative MaaS environment.
This PhD project explores cycle lane implementation from both a policymaker’s and user’s perspective, and flexible transport solutions for rural users.
This project will develop a framework/tool for forecasting future scenarios of urban freight in informing planning and regulation (transport and land use).
This PhD project will analyse archived GTFS data to identify significant inefficient road designs and exemplary designs for optimising performance
This research will focus on enhanced depiction of pedestrian and active mode interactions with vehicular traffic across a variety of road infrastructure scenarios.
This PhD research aims to investigate new methods for managing urban congestion and reducing emissions through innovative transport pricing policies.
This project aims to improve travel demand calibration and accuracy of 24 hour/ 7 days network simulation models for any hour of any day.