Scalable urban traffic control framework driven by distributed information. This project aims to develop a mathematical framework for investigating the role of information interactions between traffic signal settings and choices made by road users. Traffic control is one of the oldest and most cost-effective solutions for the worsening congestion problem in many metropolitan areas. However, through addressing fundamental mathematical challenges, further gains can be achieved to improve traffic ....Scalable urban traffic control framework driven by distributed information. This project aims to develop a mathematical framework for investigating the role of information interactions between traffic signal settings and choices made by road users. Traffic control is one of the oldest and most cost-effective solutions for the worsening congestion problem in many metropolitan areas. However, through addressing fundamental mathematical challenges, further gains can be achieved to improve traffic control and combat congestion. The expected outcome will be insights into the use of information and algorithms that can provide efficient, robust and safe traffic network management.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
Walking the city: Digital infrastructure for pedestrian mobility. Pedestrian access, flow and management are critical for urban life. However, compared to other forms of mobility pedestrian mobility is significantly more complex. Currently, various incompatible pedestrian route graphs in both outdoor and indoor environments render any analysis biased and non-transparent. This project aims to solve this problem by developing a universal and necessarily hierarchical pedestrian route graph to suppo ....Walking the city: Digital infrastructure for pedestrian mobility. Pedestrian access, flow and management are critical for urban life. However, compared to other forms of mobility pedestrian mobility is significantly more complex. Currently, various incompatible pedestrian route graphs in both outdoor and indoor environments render any analysis biased and non-transparent. This project aims to solve this problem by developing a universal and necessarily hierarchical pedestrian route graph to support critical applications such as urban walkability (health), space and asset management (guidance, flow management), and public safety (evacuation). In contrast to conventional algorithms, we will take a novel approach based on human cognition to define this universal graph and then integrate topology and geometry.Read moreRead less
Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice mode ....Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice models driven by real-world individual walking trajectory data. This project will deliver a step-change in transport planning for walking infrastructure that will lead to increased active transport and improved urban infrastructure planning, thereby resulting in significant gains in population and environmental health.Read moreRead less
The long-term effects of autonomous cars on land use, access and travel . Historically new transport technologies have significantly changed urban form in Australian cities with important business, economic, congestion, social and environmental impacts. Autonomous cars are said to revolutionise tomorrows transport but no research has yet considered long term impacts on land use and city structure. This project explores how land use and travel will change adopting innovative land use and transp ....The long-term effects of autonomous cars on land use, access and travel . Historically new transport technologies have significantly changed urban form in Australian cities with important business, economic, congestion, social and environmental impacts. Autonomous cars are said to revolutionise tomorrows transport but no research has yet considered long term impacts on land use and city structure. This project explores how land use and travel will change adopting innovative land use and transport models. Outcomes will better prepare Australia for an autonomous travel future.Read moreRead less
Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capabili ....Exploiting Geometries of Learning for Fast, Adaptive and Robust AI. This project aims to uniquely exploit geometric manifolds in deep learning to advance the frontier of Artificial Intelligence (AI) research and applications in cybersecurity and general cognitive tasks. It expects to develop new theories, algorithms, tools, and technologies for machine learning systems that are fast, adaptive, lifelong and robust, even with limited supervision. Expected outcomes will enhance Australia's capability and competitiveness in AI, and deliver robust and trustworthy learning technology. The project should provide significant benefits not only in advancing scientific and translational knowledge but also in accelerating AI innovations, safeguarding cyberspace, and reducing the burden on defence expenses in Australia.Read moreRead less
The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project ....The Benefits of Utilising Visual-Spatial Representations of Numbers . The aim of this project is to investigate how visual-spatial representations of numbers enhance practice to promote the use of retrieval-based over counting-based strategies for children learning early arithmetic. About one-third of Australian children stay reliant on counting strategies for basic arithmetic, despite these being associated with lower achievement in mathematics in later years. Expected outcomes of this project are new understandings of how problem-answer associations can be strengthened in memory and the development of tools to promote retrieval-based strategies. Potential benefits include children who are better prepared to take on higher-level mathematics in secondary school and, subsequently, more numerate citizens. Read moreRead less
Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project ....Modelling complex learning spaces. The growing use of digital tools and resources means that students' learning activities are no longer tied to unique physical places. Their work is distributed across increasingly complex mixtures of physical and digital spaces, which both shape and are shaped by students' activity. This project aims to identify productive ways of modelling the characteristics and uses of complex learning spaces in higher education. Evidence and models generated by the project aim to strengthen the logic connecting the use, management and design of learning spaces. A better understanding of the relations between pedagogy, activity and space will improve the work of architects and other designers, campus managers, university teachers and students themselves.Read moreRead less
Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom ....Does a teacher-led mindfulness intervention improve student outcomes? This project aims to determine if improving teacher knowledge and practice of mindfulness in the classroom, can lead to better child attention and school functioning outcomes during the early primary school years. Mindfulness is an approach that aims to improve attention, self-regulation, mental health, and cognitive functioning. Expected outcomes include new knowledge as to whether mindfulness can be integrated into classroom practice, how to best implement it, student benefits and cost-effectiveness. Findings will inform schools as to whether this approach can support students in making a positive transition to primary school that can place them on positive academic and well-being pathways and lead to benefits in their adulthood.Read moreRead less
Sustainable mobility: city-wide exposure modelling to advance bicycling. This project aims to develop a world-leading platform for city-wide modelling of cycling exposure. This project will provide unparalleled insights into cycling exposure by combining multiple cycling data sources through the use of advanced spatial statistical and machine learning techniques. The expected outcomes of this project are a novel inventory of cycling infrastructure, a cycling route choice modelling system and rob ....Sustainable mobility: city-wide exposure modelling to advance bicycling. This project aims to develop a world-leading platform for city-wide modelling of cycling exposure. This project will provide unparalleled insights into cycling exposure by combining multiple cycling data sources through the use of advanced spatial statistical and machine learning techniques. The expected outcomes of this project are a novel inventory of cycling infrastructure, a cycling route choice modelling system and robust predictions of cycling volumes on individual streets. This project will deliver a step change in cycling that will lead to increased cycling participation, enhanced safety, and improved infrastructure planning, thereby resulting in substantial gains in population and environmental health.Read moreRead less