Quantitative psychological theories for a dynamic world. . The dynamic world around us means we need to constantly adjust our decisions in light of ever-changing influences, both external (weather, traffic ...) and internal (fatigue, learning ...). This project aims to understand how these changes affect performance. This will have significance for basic science, and also practical benefits for applied psychology. This project will examine the dynamic nature of psychological processes in a range ....Quantitative psychological theories for a dynamic world. . The dynamic world around us means we need to constantly adjust our decisions in light of ever-changing influences, both external (weather, traffic ...) and internal (fatigue, learning ...). This project aims to understand how these changes affect performance. This will have significance for basic science, and also practical benefits for applied psychology. This project will examine the dynamic nature of psychological processes in a range of settings: simple decisions, consumer decisions, human-machine interactions, and team performance. Theory development will lead to improved understanding of underlying cognitive processes, and transforms the measurement of decisions, which is important for applied psychological investigations. Read moreRead less
Containment and Reduction of Rework in Transport Mega Projects. Mega transport projects (>$1 billion) are poorly managed during their construction with significant cost and schedule overruns and benefit shortfalls regularly being experienced. Having to perform rework has been identified as a major factor that contributes to these unintended consequences. As there has been limited research that has empirically examined rework causation, an inability to develop effective rework containment and red ....Containment and Reduction of Rework in Transport Mega Projects. Mega transport projects (>$1 billion) are poorly managed during their construction with significant cost and schedule overruns and benefit shortfalls regularly being experienced. Having to perform rework has been identified as a major factor that contributes to these unintended consequences. As there has been limited research that has empirically examined rework causation, an inability to develop effective rework containment and reduction strategies prevails. This research aims to develop a theoretical model that can be used to develop robust containment and reduction strategies to mitigate the adverse economic, productivity and safety consequences that materialize from performing rework during the construction of mega transport projects.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101310
Funder
Australian Research Council
Funding Amount
$426,918.00
Summary
Dimension-reduced Reinforcement Learning for Large-scale Fleet Management. This project aims to address the problems in large-scale fleet management to ensure the efficiency of tomorrow’s transportation models, such as on-demand ride-hailing and mobility-as-a-service. The expected outcomes of this project include improved techniques for optimising the utility of large fleets of vehicles, and particularly robust dimension-reduced reinforcement learning algorithms that are capable of handling the ....Dimension-reduced Reinforcement Learning for Large-scale Fleet Management. This project aims to address the problems in large-scale fleet management to ensure the efficiency of tomorrow’s transportation models, such as on-demand ride-hailing and mobility-as-a-service. The expected outcomes of this project include improved techniques for optimising the utility of large fleets of vehicles, and particularly robust dimension-reduced reinforcement learning algorithms that are capable of handling the complex dynamics of supply and demand in transportation. The results should advance both research and technology in academia and the transportation industry and will also provide significant benefits to Australia and the international community by enhancing the energy-efficiency of and access to the mobility of the future.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
Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-s ....Robust and Explainable 3D Computer Vision. Computer vision is increasingly relying on deep learning which is fragile, opaque and fails catastrophically without warning. This project aims to address these problems by developing new theory in graph representation of 3D geometric and image data, hierarchical graph simplification and novel modules designed specifically for deep learning over geometric graphs. Using these modules, it aims to design graph convolutional network architectures for self-supervised learning that are robust to failures and provide explainable decisions for object detection and scene segmentation. The outcomes are expected to advance theory in robust deep learning and benefit 3D mapping, surveying, infrastructure monitoring, transport and robotics industries.Read moreRead less
Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learni ....Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learning architectures that are inherently robust. The outcomes of this project will increase the security and reliability of computer vision by detecting, reporting and nullifying such attacks and will benefit the general public and industry on many fronts.Read moreRead less
Promoting active travel and public transport for a post-pandemic world. In many major cities, COVID-19 stimulated the provision of open streets, pop up bike lanes and widened pedestrian access, prompting unprecedented increases cycling and walking. While this type of infrastructure has always been supported by urban planners and designers, the pandemic has served as a vital inflection point, enabling cities to pursue long-term sustainable transport initiatives, including investment in Active Tra ....Promoting active travel and public transport for a post-pandemic world. In many major cities, COVID-19 stimulated the provision of open streets, pop up bike lanes and widened pedestrian access, prompting unprecedented increases cycling and walking. While this type of infrastructure has always been supported by urban planners and designers, the pandemic has served as a vital inflection point, enabling cities to pursue long-term sustainable transport initiatives, including investment in Active Travel (AT). There is an opportunity to promote AT as part of an integrated transport strategy, and to develop tools for the robust evaluation of AT impacts to inform future investment strategies. This proposal will provide our partner organisation Transport for New South Wales (with the knowledge required to achieve this.
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Discovery Early Career Researcher Award - Grant ID: DE220100052
Funder
Australian Research Council
Funding Amount
$437,020.00
Summary
Impacts of the apartment boom on public transport in Australian cities. This project aims to investigate the impacts of high density housing on public transport use and service provision to directly inform policy and practice. Recent growth in high density housing along public transport corridors is associated with overcrowded public transport services in Australian cities, yet this complex and interconnected relationship is not well understood. This project expects to generate new knowledge in ....Impacts of the apartment boom on public transport in Australian cities. This project aims to investigate the impacts of high density housing on public transport use and service provision to directly inform policy and practice. Recent growth in high density housing along public transport corridors is associated with overcrowded public transport services in Australian cities, yet this complex and interconnected relationship is not well understood. This project expects to generate new knowledge in the field of transport and land use integration and produce much needed cross-sectional and longitudinal evidence of the impacts of the apartment boom on public transport. Anticipated benefits include reduced overcrowding on public transport, improved travel choices and enhanced liveability in Australian cities.Read moreRead less
Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This pro ....Personalised public transport. This project aims to address urban congestion by utilising people’s travel plans to coordinate journeys. The project expects to generate new knowledge in scalable optimisation, based on innovative modelling of urban transport, and tested on historical data from Melbourne. The expected outcomes of the project are an active transport database and optimised mode choice and routing system, with predicted reductions in congestion based on simulation of its use. This project aims to design an urban trip advisory system that could be followed by automated vehicles as well as human drivers, to reduce the financial and environmental cost of current urban congestion.Read moreRead less