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Australian State/Territory : QLD
Field of Research : Civil Engineering
Socio-Economic Objective : Road safety
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  • Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0233830

    Funder
    Australian Research Council
    Funding Amount
    $350,000.00
    Summary
    Intelligent Transport and Vehicle Systems Research Laboratory. This proposal seeks funding to establish a world class Intelligent Transport and Vehicle Systems Research Laboratory. The Laboratory is aimed at developing and evaluating advanced traffic management and advanced vehicle technologies to improve the safety and efficiency of existing transport systems. The laboratory will comprise high-end computing and traffic simulation workstations with live real-time connections to a test-bed. The l .... Intelligent Transport and Vehicle Systems Research Laboratory. This proposal seeks funding to establish a world class Intelligent Transport and Vehicle Systems Research Laboratory. The Laboratory is aimed at developing and evaluating advanced traffic management and advanced vehicle technologies to improve the safety and efficiency of existing transport systems. The laboratory will comprise high-end computing and traffic simulation workstations with live real-time connections to a test-bed. The live link to the test-bed is a unique feature of the proposed facility. It will provide researchers with access to field data from sensors, videos and detectors to test prototypes of systems and evaluate their performance under live traffic conditions.
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    Funded Activity

    Linkage Projects - Grant ID: LP0883807

    Funder
    Australian Research Council
    Funding Amount
    $423,585.00
    Summary
    Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will .... Artificial Intelligence Based Deterioration Model for Development of Bridge Network Maintenance Strategy. The proposed AI-based methodology in conjunction with a Bridge Management System can tailor-make bridge deterioration models for a given bridge authority. The models so produced will enable effective BMS implementation which generates missing inspection records of past years, establishes optimal MR&R strategies and then reliably forecasts future bridge condition ratings. The methodology will be verified using available bridge datasets of QDMR and GCCC. The methodology is applicable to other bridge authorities throughout Australia and internationally to maintain ageing bridge stock.
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    Funded Activity

    Linkage Projects - Grant ID: LP0233238

    Funder
    Australian Research Council
    Funding Amount
    $112,725.00
    Summary
    Assessing the full impacts of high efficiency heavy vehicles in urban traffic networks using new analytical tools. Significant economic benefits result from new innovative heavy vehicles, which are able to carry up to twice the payload of standard semi-trailers. In addition, those vehicles have the potential to reduce overall accidents and evironmental degradation. Those benefits need to be traded-off against the impacts on other road users. This research will improve the operation of such ve .... Assessing the full impacts of high efficiency heavy vehicles in urban traffic networks using new analytical tools. Significant economic benefits result from new innovative heavy vehicles, which are able to carry up to twice the payload of standard semi-trailers. In addition, those vehicles have the potential to reduce overall accidents and evironmental degradation. Those benefits need to be traded-off against the impacts on other road users. This research will improve the operation of such vehicles in regional centres by producing: (1) an assessment methodology to deal with options for network efficiency gains which will capture the full impacts; and (2) a computer modelling tool based on fundamental research to quantify those impacts, in terms of delays and accident rates.
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