Ubiquitous Data Mining and Situation-Awareness for Improving Road Safety. Road crashes cost Australia $15 billion a year and 95% of these are attributed to drivers' errors. Risk assessment is at the core of the road crash problem. This innovative project develops a computational model that analyses situational driver behaviour and proposes real-time countermeasures to minimise fatalities/casualties. We develop and evaluate a novel Intelligent Transport System that assesses and acts upon drivers ....Ubiquitous Data Mining and Situation-Awareness for Improving Road Safety. Road crashes cost Australia $15 billion a year and 95% of these are attributed to drivers' errors. Risk assessment is at the core of the road crash problem. This innovative project develops a computational model that analyses situational driver behaviour and proposes real-time countermeasures to minimise fatalities/casualties. We develop and evaluate a novel Intelligent Transport System that assesses and acts upon drivers' risks. This multidisciplinary project integrates recent models of data mining, context-awareness computing, physiological metrics, ubiquitous computing, driver distraction models, risk perception and road safety. This project yields a new understanding of driver behaviour and countermeasures in risk situations.Read moreRead less
Domain-driven information, quality assurance and interoperability for road transport systems. This project addresses the ever increasing need for improved information quality in the area of road transport and urban planning. Public bodies, like State and Federal authorities, require highly accurate sets of personal records as they are central authorities for the identification of individuals. This project will develop techniques for the enhancement of these records.
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Real-time Analytics on Urban Trajectory Data for Road Traffic Management. This project aims to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traff ....Real-time Analytics on Urban Trajectory Data for Road Traffic Management. This project aims to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traffic demand and network congestion propagation. This project seeks to develop innovative technologies to use a wide variety of data sources, especially massive trajectories of vehicles moving across the network, to better understand people's travel demands and road usage patterns and thus better manage the transport system.
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Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the effici ....Managing uncertainty in RFID traceability networks. Australia suffers 5.4 million cases of food-borne illness every year, which leads to 2.1 million days of lost work, 1.2 million people visiting a doctor, and 120 deaths annually. This has revealed the urgent need for improved ways of locating and recalling problematic products that have been released into the community. The project will develop novel techniques driven by Radio Frequency Identification (RFID) technology for improving the efficiency and accuracy of product tracking in distribution networks. This project will place Australia at the forefront of RFID research. It will also be an excellent vehicle for educating young researchers and engineers in Australia.Read moreRead less