Intention-aware cooperative driving behaviour model for Automated Vehicles. This project aims to investigate humans' cooperation with automated systems by conceptualising joint intention awareness. This project expects to generate knowledge about a new cooperative driving behaviour model for automated vehicles, utilising a transdisciplinary approach that mixes human-centric methods with deep learning techniques. Intended outcomes are new joint intention awareness theory, new interface for automa ....Intention-aware cooperative driving behaviour model for Automated Vehicles. This project aims to investigate humans' cooperation with automated systems by conceptualising joint intention awareness. This project expects to generate knowledge about a new cooperative driving behaviour model for automated vehicles, utilising a transdisciplinary approach that mixes human-centric methods with deep learning techniques. Intended outcomes are new joint intention awareness theory, new interface for automated vehicles, new methodology for cooperative behaviour research, and enhanced research capacity. The expected significant benefits are for automated systems to become more predictable, acceptable, readable and safer to use by everyday people.Read moreRead less
Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving. This project aims to reduce risky driving behaviours through novel augmented reality applications for three-dimensional head-up displays, making safe driving more engaging so that drivers will take less risk. Over 1 million people are killed and 50 million are seriously injured on roads each year worldwide. Risky driving behaviours (speeding and distracted driving) are major causes. This project intends to produce novel i ....Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving. This project aims to reduce risky driving behaviours through novel augmented reality applications for three-dimensional head-up displays, making safe driving more engaging so that drivers will take less risk. Over 1 million people are killed and 50 million are seriously injured on roads each year worldwide. Risky driving behaviours (speeding and distracted driving) are major causes. This project intends to produce novel in-car interaction design implementations, provide important visual design guidelines for future display technologies, and provide novel road safety interventions.Read moreRead less
Highly Multiplexed Fibre Sensor Systems for Structural Health Monitoring and Risk Assessment of Critical Transport Infrastructures. Safeguarding critical transport infrastructures is very much in the interest of Australian government and people. This project is to develop advanced photonic and telecommunication technologies for timely and reliably acquiring and processing key structural performance information. This will reduce structural failures and maintenance costs with reliable data of stru ....Highly Multiplexed Fibre Sensor Systems for Structural Health Monitoring and Risk Assessment of Critical Transport Infrastructures. Safeguarding critical transport infrastructures is very much in the interest of Australian government and people. This project is to develop advanced photonic and telecommunication technologies for timely and reliably acquiring and processing key structural performance information. This will reduce structural failures and maintenance costs with reliable data of structure health monitoring and risk assessment.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101542
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Risky Gadgets to the Rescue: Designing Personal Ubicomp Devices to Foster Safer Driving Behaviours in Young Males. Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving or distractions. This project aims to design innovative ubiquitous computing technologies that make safe driving more stimulating and pleasurable. This research will inform the future design of personal ubiquitous devices ....Risky Gadgets to the Rescue: Designing Personal Ubicomp Devices to Foster Safer Driving Behaviours in Young Males. Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving or distractions. This project aims to design innovative ubiquitous computing technologies that make safe driving more stimulating and pleasurable. This research will inform the future design of personal ubiquitous devices that pose a threat to road safety, by replacing the stimuli from risky driving with safer stimuli and simulating risk to increase risk perception when it is actually not present. This project aims to reduce risky driving behaviours, and, in the process, advance our knowledge about the role of boredom in the road safety context.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
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.Read moreRead less
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.
Read moreRead less