iMOVE projects 31 to 40: Powering on

Enhanced vehicle detection at traffic signals and on smart freeways

The purpose of this project is to investigate alternative vehicle detection technologies for traffic signal control and smart freeway operations through a comparative desktop analysis and field trials of shortlisted technologies at two locations (intersection and freeway).

This research will be used to inform decisions on future traffic network investments, primarily through the future enhanced detection installation business case and delivery strategy, particularly for future smart freeway projects.

Project participants on this are the University of Western Australia, and Main Roads Western Australia.

Optimising signal control in CAV and VRU mixed environments

The aim of this project is to explore how traffic controls can be optimised to accommodate both human-driven vehicles and autonomous vehicles, while considering vulnerable road users, such as pedestrians and cyclists, at intersections.

This PhD project is being run by the University of NSW.

Evaluating loading dock capacity in new developments

This project seeks to provide an improved and reliable methodology for forecasting demand to establishing loading dock requirements in new developments. An aim of this project is ultimately to make a method accessible for use by stakeholders to assess a new development’s loading dock requirements in Sydney and other Australian cities.

Participants on this project are Transport for NSW, and the University of Melbourne.

Multimodal operation of smart intersections

This PhD research project aims to develop a model/platform that can utilise real-time feeds of all mode movements from our smart intersections and optimise the signal control to minimise safety risks, all while maintaining an efficient flow of vehicular traffic at the network level.

Participants on this project are the University of Melbourne, and RACQ.

Demand management/estimation in large-scale traffic networks

The aim of this study is set to develop demand management and demand estimation tools for large-scale traffic networks. Two objectives are accomplished in this project where we focus on developing demand management and demand estimation strategies for large-scale traffic networks by incorporating the macroscopic fundamental diagram-based traffic dynamics.

This project is being supervised by the University of Queensland.

Macroscopic Fundamental Diagram: Measuring flow and density

This research presents a novel, network-wide approach to identify critical links and estimate average traffic flow and density. The proposed model estimates the Macroscopic Fundamental Diagram (MFD) using flow and density measurements from those critical links, which constitute only a small subset of all the links in the network.

This project is being supervised by the University of Queensland.

Risks in blockchain-integrated container shipping systems

This research investigates the situation of Container Shipping Operational Risk (CSOR) upon the application of blockchain technology by the process of risk identification to risk assessment. It develops and validates novel quantitative tools for risk analysis, such as multiple-event risk scenarios analysis and uncertainty quantification analysis.

This project is being supervised by the University of Tasmania.

Econometrics, land use inputs, and strategic transport models

The purpose of this project is to improve the interactions between urban transport and land use systems, especially at the level of individual decision makers (households and enterprises). It will approach this through the provision of advanced econometric support in a practical implementation of a bid-rent model structure and parameter estimation as part of a newly established land use model. This will produce robust and high-quality household and business activity inputs to transport modelling.

Participants on this project are the University of Western Australia, Main Roads Western Australia, Department of Transport (WA), and the Department of Planning Lands and Heritage Western Australia.

Transformative commercial urban delivery solutions

This research aims to identify and evaluate new solutions for commercial urban deliveries to meet the demand of last-mile and surging e-commerce markets. Traffic simulation models will be developed using real-world freight demands. Solutions modelled and evaluated will include electric vehicles for night-time deliveries, urban consolidation centres, load pooling, route optimisation, active mode deliveries, autonomous ground vehicles and drones.

This PhD project is being supervised by Professor Hussein Dia, of the Swinburne University of Technology.

Vehicular network architecture using the 5G standard

This PhD research, undertaken at the University of Newcastle, concentrates on the development of an ad hoc vehicular network architecture using the PC5 interface of the LTE (Long Term Evolution) standard.