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Current Selection
Scheme : Discovery Projects
Socio-Economic Objective : Road Public Transport
Status : Closed
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  • Researchers (19)
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  • Funded Activity

    Discovery Projects - Grant ID: DP160104081

    Funder
    Australian Research Council
    Funding Amount
    $440,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP110104738

    Funder
    Australian Research Council
    Funding Amount
    $153,949.00
    Summary
    New paradigms for urban public transport planning in Australia: assessing the capacity of institutions and infrastructure. Current urban transport policies cannot be sustained in the face of climate change, peak oil and economic instability: dramatic increases in public transport use will require new standards of service delivery. This project will use international experience to shape new approaches to planning public transport in our largest cities.
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    Funded Activity

    Discovery Projects - Grant ID: DP120100201

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP120102392

    Funder
    Australian Research Council
    Funding Amount
    $285,000.00
    Summary
    Innovative urban traffic congestion solutions: optimising road space using networks of multi-class priority lanes. This project strengthens national approaches to a pervasive Australian problem; growing traffic congestion deteriorating liveability, environmental health and economic performance of the cities. This project improves approaches for traffic priority design to improve the efficiency of several class of vehicles and therefore, reducing traffic congestion.
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    Funded Activity

    Discovery Projects - Grant ID: DP200101116

    Funder
    Australian Research Council
    Funding Amount
    $430,000.00
    Summary
    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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    Funded Activity

    Discovery Projects - Grant ID: DP170103341

    Funder
    Australian Research Council
    Funding Amount
    $460,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP180103096

    Funder
    Australian Research Council
    Funding Amount
    $407,947.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP170101628

    Funder
    Australian Research Council
    Funding Amount
    $528,000.00
    Summary
    Towards efficient processing of big graphs. This project aims to develop theory and techniques for efficient and scalable processing of Big Graph, a major field in Big Data. The project will focus on primitive graph queries covering many applications. Anticipated outcomes include a set of theories, indexing and data processing (including distributed and approximate) techniques. The success of the project is expected to contribute to the technology development and the scientific foundation of Big .... Towards efficient processing of big graphs. This project aims to develop theory and techniques for efficient and scalable processing of Big Graph, a major field in Big Data. The project will focus on primitive graph queries covering many applications. Anticipated outcomes include a set of theories, indexing and data processing (including distributed and approximate) techniques. The success of the project is expected to contribute to the technology development and the scientific foundation of Big Graph processing.
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    Funded Activity

    Discovery Projects - Grant ID: DP170100420

    Funder
    Australian Research Council
    Funding Amount
    $310,000.00
    Summary
    Business location decisions. This project aims to develop a forecasting model system for economic planning that integrates business (re-) location and co-location choices. Improved transport infrastructure connects places and can influence the location of businesses. This project will use forecasting models to quantify the drivers of firm location decisions linked to an integrated strategic transport and land use modelling system. This project expects to provide guidance for transport investment .... Business location decisions. This project aims to develop a forecasting model system for economic planning that integrates business (re-) location and co-location choices. Improved transport infrastructure connects places and can influence the location of businesses. This project will use forecasting models to quantify the drivers of firm location decisions linked to an integrated strategic transport and land use modelling system. This project expects to provide guidance for transport investment that brings gains in productivity to industry and the economy and wellbeing to individuals and society.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100909

    Funder
    Australian Research Council
    Funding Amount
    $420,000.00
    Summary
    Integrating Attribute Decision Heuristics into Travel Choice Models that accommodate Risk Attitude and Perceptual Conditioning. This proposal has the specific objective of integrating two disconnected literatures that are having a major influence on the behavioural and statistical performance of discrete choice models in travel choice modelling. These fields are attribute processing strategies and the conditioning of the marginal utility of attributes by risk attitude and perceptual conditioning .... Integrating Attribute Decision Heuristics into Travel Choice Models that accommodate Risk Attitude and Perceptual Conditioning. This proposal has the specific objective of integrating two disconnected literatures that are having a major influence on the behavioural and statistical performance of discrete choice models in travel choice modelling. These fields are attribute processing strategies and the conditioning of the marginal utility of attributes by risk attitude and perceptual conditioning. These two major developments have not been jointly integrated into a behaviourally richer representation of choice making. Given the encouraging evidence from both literatures, the research will determine more precisely the benefits in terms of improved estimates of willingness to pay for specific attributes and also increased predictive power.
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