Understanding impact of autonomous vehicles on behaviour and interactions. Understanding impact of autonomous vehicles on behaviour and interactions. This project aims to explore three human factor issues critical to the successful deployment of automated vehicles: factors influencing driver choice of automated vehicle control; interactions between automated and manually controlled vehicles; and driver detection, recognition, and reaction to automated vehicle system failures. Automated vehicles ....Understanding impact of autonomous vehicles on behaviour and interactions. Understanding impact of autonomous vehicles on behaviour and interactions. This project aims to explore three human factor issues critical to the successful deployment of automated vehicles: factors influencing driver choice of automated vehicle control; interactions between automated and manually controlled vehicles; and driver detection, recognition, and reaction to automated vehicle system failures. Automated vehicles are predicted to be transformative, but their ultimate success and expected societal benefits will depend on drivers’ trust in them and on how people choose to use and interact with them. Insights from this research should prepare our society for more automated vehicles on the roadways.Read moreRead less
A Road Out of Motion Sickness in Autonomous Vehicles. Autonomous vehicles have found to provide significant improvements in safety and efficiency, as well as the potential to comfortably engage in other activities including work and entertainment. Motion sickness is particularly a significant source of concern in this regard, with factors ranging from demographics, vehicle kinematics to in-vehicle designs affecting the likelihood of discomfort. This study aims to (1) understanding factors induci ....A Road Out of Motion Sickness in Autonomous Vehicles. Autonomous vehicles have found to provide significant improvements in safety and efficiency, as well as the potential to comfortably engage in other activities including work and entertainment. Motion sickness is particularly a significant source of concern in this regard, with factors ranging from demographics, vehicle kinematics to in-vehicle designs affecting the likelihood of discomfort. This study aims to (1) understanding factors inducing motion sickness in AVs (2) Evaluating individuals’ preferences between comfort and travel attributes (including in-vehicle tasks) (3) Develop and evaluate mitigation strategies for motion sickness in AVs. Insights from this research will help improve adoption of automated vehicles on the roadways.
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Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Integrating Mobility on Demand in urban transport infrastructures. Australia’s major cities are substantially challenged for public transport services due to the dispersed and low population densities, and thus, roads are at or beyond their capacity. Smarter demand-responsive public transport services are therefore needed. This project studies the viability of such a service under a variety of scenarios.
Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. Thi ....Stable on-demand optimization for workforce and fleet logistics management. This project aims to conceive, develop and deploy innovative methodologies for stable on-demand workforce management and fleet logistics based on advanced decision-support systems. The outcome of this project will provide a new cloud-based real-time Optimisation Software-as-a-Service (OSaaS) platform that allows businesses to improve their productivity while reducing operating costs and their environmental footprint. This is expected to support the manufacturing, retail, delivery and mobile fleets industries.Read moreRead less
A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driv ....A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driving models. The project will lead to two innovations: in theory design an attack detection and prevention ecosystem for autonomous driving and in application implement a safety analysis toolset for industry-scale autonomous systems.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.
Methodologies for the incorporation of congestion propagation and system reliability into transport network models for consistent multi-scale planning. This project will improve the capabilities of transport planning techniques. Specifically, new methods will be introduced, which improve the realism of regional congestion modelling, and the mathematical representation of traveller decision-making, thereby permitting an improved long-term transport plan.
Multiliteracy testing: a criterion-referenced tool to assess secondary students’ multiliteracy learning within a technology-rich, multimodal domain. Evidence shows that while multimodal learning in schools is occurring, a valid measurement and diagnostic tool to provide reliable scores and accurate diagnostic information does not exist. This project aims to develop a criterion-referenced tool to measure students' multiliteracy learning within technology-rich, multimodal domains.
International collaboration in teaching and learning of Einsteinian physics. Following a previous project that showed that it is possible and beneficial to teach the modern Einsteinian paradigm of space, time, matter, light and gravity to students as young as 8 years old, this project aims to test and evaluate a seamless progression of learning modern physics through primary and secondary school. It will sequence, integrate and test research-informed teaching and learning materials, and assessme ....International collaboration in teaching and learning of Einsteinian physics. Following a previous project that showed that it is possible and beneficial to teach the modern Einsteinian paradigm of space, time, matter, light and gravity to students as young as 8 years old, this project aims to test and evaluate a seamless progression of learning modern physics through primary and secondary school. It will sequence, integrate and test research-informed teaching and learning materials, and assessment instruments developed through a 7-nation collaboration. Research across 24 schools will be reviewed by a panel drawn from professional organisations and curriculum authorities, and learning resources will be widely disseminated, with view to worldwide introduction of Einsteinian science at school.Read moreRead less