We have partnered with iMOVE Australia, Insurance Australia Group and Skedgo on a MaaS trial in Sydney with the aim to advance the understanding of the role that MaaS can play in both improving the travellers' experience of using multiple complementary transport services (in terms of cost, travel time, convenience, health benefits and perceived safety), and in contributing to improvements in broader community benefits (such as better air quality, reduced congestion and greenhouse gas emission savings) by providing a pertinent alternative to owning and using private vehicles.
We have partnered with the Centre of Excellence in Bus Rapid Transit (BRT) Development with the goal of developing a new framework for planning, design, financing, implementation and operation of BRT in different urban areas, giving clear guidelines to decision makers on when and how BRT projects can effectively enhance mobility and meet accessibility needs.
Implemented in Santiago, Chile, BRT is financed by the Volvo Research and Educational Foundations working as a consortium of five institutions:
We have partnered with Travel Choice Simulation Laboratory (TRACSLab) to improve the capabilities of transport planning techniques by developing new methods to improve the realism of regional congestion modelling, and the mathematical representation of traveller decision-making, thereby permitting an improved long-term transport plan.
Visit the TRACSLab website for more information.
We are working to deliver more accurate estimates of choice behaviour by reducing biases due to choice task complexity in surveys as well as design artefacts.
Extracting "true" preferences is challenging, not only due to possible hypothetical bias, but also due to increasingly complex choice tasks and the existence of design artefacts. This project will investigate the latter two in the context of marketing, transport, health and environmental economics and propose new methodologies to extract preferences that more closely reflect true behaviour in real markets.
We are working to find simpler and more accurate approaches to measuring the impacts of new cycling infrastructure, to be applied to a new bicycle path to be built by the City of Sydney. This will demonstrate the full transport, environmental, health, and economic impacts on the community.
Automated vehicles are predicted to be transformative, but their ultimate success and expected societal benefits will depend on drivers’ trust in them as well as how people choose to use and interact with them.
We are exploring three human-factor issues critical to the successful deployment of automated vehicles:
Insights from this research should prepare our society for more automated vehicles on roadways.
We are working to provide strategies to address key transport-related barriers in order to enable people living with disability to participate in the workforce.
A state-of-the-art planning and evaluation capability, encompassing demand forecasts, cost-benefit analysis and economic impact to assess the merits of major infrastructure such as roads, airports, public transport (heavy and light rail, and bus and ferry systems), as well as precinct investments such as new housing and industry and business stock.
Integrating attribute processing strategies and the conditioning of the marginal utility of attributes by risk attitude and perceptual conditioning to improve estimates of willingness-to-pay for specific attributes and also increased predictive power.
Improving practical behavioural models to predict responses to transport policies in order to assist in better decision-making; merging methods from stated choice surveys, experimental economics, and naturalistic driving simulators in order to better investigate travel choice behaviour in realistic environments.
Looking to nature for new solutions to supply chain design and management problems: through experiments on ants and slime moulds, this project will uncover the secrets of biological resilience, and use this insight to develop new algorithms for supply chain design and management.