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Discovery Early Career Researcher Award - Grant ID: DE130100205
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Optimisation of transit priority in a transportation network. This project is aimed at developing an optimised approach to combine various types of public transport priority in an urban network which can be used by transport planners to increase the efficiency of traffic movements and reduce traffic congestion. The case study is the network of Brisbane including all arterial and local roads.
Funding on the line: public transport financing and property value capture. This project aims to develop property value capture schemes that would provide alternative funding for public transport infrastructure. It plans to model the timing and spatial patterns of property value uplift from recent investments in rail, busways and ferries in Queensland and New South Wales. It then intends to conduct a survey of Australian stakeholders and discrete choice modelling to determine willingness-to-pay. ....Funding on the line: public transport financing and property value capture. This project aims to develop property value capture schemes that would provide alternative funding for public transport infrastructure. It plans to model the timing and spatial patterns of property value uplift from recent investments in rail, busways and ferries in Queensland and New South Wales. It then intends to conduct a survey of Australian stakeholders and discrete choice modelling to determine willingness-to-pay. This data is then expected to be used to develop an institutionally, legally and politically feasible scheme for implementation in Australia, focused on cases including extension to the Gold Coast light rail network.Read moreRead less
Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The exp ....Managing the risks posed by Artificial General Intelligence. It is widely acknowledged that a failure to implement appropriate controls for the next generation of Artificial Intelligence, Artificial General Intelligence (AGI), could have catastrophic consequences, including in the worst case - the extinction of the human race. This research aims to forecast the risks associated with AGI systems and identify the controls required to ensure that risks and existential threats are minimised. The expected outputs will provide designers, organisations, regulators and governments with a framework to support the design, implementation, and management of safe and efficient AGI systems. This will ensure that the potential far-reaching benefits of AGI are realised without undue threat to society.Read moreRead less