Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to deve ....Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to develop unsupervised learning algorithms to infer high-level driver behaviours, intent and contextual information to automatically evaluate levels of risk under complex driving scenarios. It plans to validate the results using naturalistic driving datasets taken in large-scale deployments around the world. This innovation may improve automotive safety and facilitate the deployment of autonomous vehicles.Read moreRead less
Valuation of service reliability and crowding under risk and uncertainty: neglected drivers of demand for public transport. The reliability of public transport services, and the amount of crowding at stations and also on trains and on buses, have come under strong criticism. This study identifies the role that improved service reliability and reduced crowding play in influencing the switch from car to public transport for the commute.
Cohesive Subgraph Discovery on Big Bipartite Graphs. This project aims to develop novel technology for efficient and scalable cohesive subgraph discovery on big bipartite graphs, including new theories, indexing techniques, and data processing algorithms. We anticipate addressing key challenges and laying scientific foundations of big graph computation, as well as delivering high-impact technologies. The success of the project will directly benefit the key applications in Australia such as cyber ....Cohesive Subgraph Discovery on Big Bipartite Graphs. This project aims to develop novel technology for efficient and scalable cohesive subgraph discovery on big bipartite graphs, including new theories, indexing techniques, and data processing algorithms. We anticipate addressing key challenges and laying scientific foundations of big graph computation, as well as delivering high-impact technologies. The success of the project will directly benefit the key applications in Australia such as cyber-security, health, bio-informatics, social networks, and E-commerce. The success of the project will also facilitate the training of PhD graduates and postdoctoral research associates in the area of Big Data.
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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
Trustworthy positioning for intelligent transport systems. This project aims to develop a holistic approach for reliable positioning for Intelligent Transport Systems (ITS). This project will address the challenges of integrity monitoring in ITS when using satellite-based technology, its integration with other sensors, and when supported by the proposed Australia National Positioning Infrastructure. It will consider Australian geography, large area, and sparse population, and emphasise rural tra ....Trustworthy positioning for intelligent transport systems. This project aims to develop a holistic approach for reliable positioning for Intelligent Transport Systems (ITS). This project will address the challenges of integrity monitoring in ITS when using satellite-based technology, its integration with other sensors, and when supported by the proposed Australia National Positioning Infrastructure. It will consider Australian geography, large area, and sparse population, and emphasise rural transport. Expected primary outputs include algorithms, a detailed analysis of required systems and recommendations that will help prepare Australia for the importation of self-driving vehicles.Read moreRead less
Efficient processing of large scale multi-dimensional graphs. This project aims to develop novel approaches to process large scale multi-dimensional graphs. The project will focus on the three most representative types of problems against multi-dimensional graphs, namely cohesive subgraph computation, frequent subgraph mining, and subgraph matching. The project outcome will include a set of new theories, novel indexing and data processing techniques, including distributed and single node computa ....Efficient processing of large scale multi-dimensional graphs. This project aims to develop novel approaches to process large scale multi-dimensional graphs. The project will focus on the three most representative types of problems against multi-dimensional graphs, namely cohesive subgraph computation, frequent subgraph mining, and subgraph matching. The project outcome will include a set of new theories, novel indexing and data processing techniques, including distributed and single node computation. The success of the project will significantly contribute to the technology development and the scientific foundation of big graph processing.Read moreRead less
Integrating network modelling with observed choice data for multi-criteria optimisation of complex car share systems: cost, mobility and transit usage. This project will develop methods to determine an efficient car share system, which includes optimal location, one-way car sharing, and how carshare influences the broader transport system. By adopting such new comprehensive methods, the overall transport system will benefit through potential improvements in public transit usage.
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
The role of vegetation and associated root suction and reinforcement on the stabilisation of transport corridors and sloping ground. The project will promote the concept of green corridors and green hills for stabilising unstable soils through optimum root reinforcement and suction. The improved load capacity, control of unacceptable soil movement and slope stabilisation will provide an efficient platform for sustainable development of transport and building infrastructure.