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Socio-Economic Objective : Expanding Knowledge in Engineering
Research Topic : interaction
Australian State/Territory : NSW
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP220102019

    Funder
    Australian Research Council
    Funding Amount
    $468,525.00
    Summary
    Shared-space interactions between people and autonomous vehicles. This project aims to understand how autonomous vehicles in urban environments need to interact with the people that they share those spaces with. Autonomous vehicles that are able to operate in shared spaces, such as campuses and pedestrian zones, promise to improve urban life. However, their uptake depends heavily on public acceptance as they operate in close proximity to people. The project investigates whether people are more l .... Shared-space interactions between people and autonomous vehicles. This project aims to understand how autonomous vehicles in urban environments need to interact with the people that they share those spaces with. Autonomous vehicles that are able to operate in shared spaces, such as campuses and pedestrian zones, promise to improve urban life. However, their uptake depends heavily on public acceptance as they operate in close proximity to people. The project investigates whether people are more likely to trust the technology and feel safe if they are able to understand how the system makes decisions and to directly influence its behaviour. Outcomes are expected to promote safe behaviour around urban robotic applications and accelerate the uptake of autonomous systems in Australia’s cities.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP200100336

    Funder
    Australian Research Council
    Funding Amount
    $274,933.00
    Summary
    Design guidelines for safety-critical controllers in high-risk environments. This project aims to generate novel product design guidelines for developing safer controllers for use by potentially stressed individuals in high-risk situations. It will do this by generating specific insights and verifying generalisable solutions from the context of total artificial heart recipients –who must engage with critical controllers constantly. This project expects to generate new knowledge in design by esta .... Design guidelines for safety-critical controllers in high-risk environments. This project aims to generate novel product design guidelines for developing safer controllers for use by potentially stressed individuals in high-risk situations. It will do this by generating specific insights and verifying generalisable solutions from the context of total artificial heart recipients –who must engage with critical controllers constantly. This project expects to generate new knowledge in design by establishing a new research topic around an under-examined user cohort. Expected outcomes of this project include interaction design theory developments and improved controller design techniques. This should provide significant benefits and competitive advantages by lowering stress and improving safety across a range of contexts.
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    Funded Activity

    Discovery Projects - Grant ID: DP180100670

    Funder
    Australian Research Council
    Funding Amount
    $354,592.00
    Summary
    A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general fra .... A neural fuzzy fusion engine for human-machine autonomous systems. This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The project will develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general framework to facilitate human-machine interaction and enable better collaborative decisions in HMAS. The outcomes will benefit human-centric automation systems in general and next-generation autonomous vehicles in particular, which will contribute to the Australian economy.
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