Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control dec ....Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control decisions in real-time. The expected benefits are profound; the developed algorithms and platform will significantly reduce traffic congestion, travel delays and safety risks for all modes of transport, especially for vulnerable road users (e.g. pedestrians and cyclists).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
Industrial Transformation Training Centres - Grant ID: IC230100001
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Training Centre for Automated Vehicles in Rural and Remote Regions. The Centre will build skills and capability to test and deploy safe, socially acceptable, automated vehicles (AV) for rural, regional and remote Australian public roads, where manufacturing, agriculture, mining and defence industries face significant challenges of driver shortages, rising costs, long distances, rough roads, and environmental impacts. The centre will unite technology providers, regulators, government and end ....ARC Training Centre for Automated Vehicles in Rural and Remote Regions. The Centre will build skills and capability to test and deploy safe, socially acceptable, automated vehicles (AV) for rural, regional and remote Australian public roads, where manufacturing, agriculture, mining and defence industries face significant challenges of driver shortages, rising costs, long distances, rough roads, and environmental impacts. The centre will unite technology providers, regulators, government and end users with world-leading interdisciplinary researchers to create new human-AV systems, datasets, frameworks, case studies, platforms, and a vastly upskilled workforce. This will reduce transport costs, increase capacity, boost supply chain efficiency and resilience, improve road safety, and elevate Australian capability.Read moreRead less
Sustainable mobility: city-wide exposure modelling to advance bicycling. This project aims to develop a world-leading platform for city-wide modelling of cycling exposure. This project will provide unparalleled insights into cycling exposure by combining multiple cycling data sources through the use of advanced spatial statistical and machine learning techniques. The expected outcomes of this project are a novel inventory of cycling infrastructure, a cycling route choice modelling system and rob ....Sustainable mobility: city-wide exposure modelling to advance bicycling. This project aims to develop a world-leading platform for city-wide modelling of cycling exposure. This project will provide unparalleled insights into cycling exposure by combining multiple cycling data sources through the use of advanced spatial statistical and machine learning techniques. The expected outcomes of this project are a novel inventory of cycling infrastructure, a cycling route choice modelling system and robust predictions of cycling volumes on individual streets. This project will deliver a step change in cycling that will lead to increased cycling participation, enhanced safety, and improved infrastructure planning, thereby resulting in substantial gains in population and environmental health.Read moreRead less
Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project ....Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project are a family of new context-aware techniques to verify and validate complex behaviours in autonomous driving. This should provide significant benefits, such as safe autonomous driving systems and the improved journey experience and security for road users.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170101180
Funder
Australian Research Council
Funding Amount
$327,900.00
Summary
Understanding and preventing road deaths using coronial investigations. This project aims to study coronial death investigations of fatal road crashes in Australia using public health and road safety theoretical frameworks. Fatal road crashes are sudden, unexpected and violent. Each fatality has a lasting effect resulting in immeasurable emotional costs and a financial burden in excess of $3.8 billion per year. Intended outcomes will contribute to understanding of fatal road crashes including pr ....Understanding and preventing road deaths using coronial investigations. This project aims to study coronial death investigations of fatal road crashes in Australia using public health and road safety theoretical frameworks. Fatal road crashes are sudden, unexpected and violent. Each fatality has a lasting effect resulting in immeasurable emotional costs and a financial burden in excess of $3.8 billion per year. Intended outcomes will contribute to understanding of fatal road crashes including pre-crash social factors (e.g. alcohol/drug use and dependence, unemployment, age), the use and effect of coronial recommendations on road safety policy and practice, and preventing deaths on Australian roads.Read moreRead less
Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice mode ....Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice models driven by real-world individual walking trajectory data. This project will deliver a step-change in transport planning for walking infrastructure that will lead to increased active transport and improved urban infrastructure planning, thereby resulting in significant gains in population and environmental health.Read moreRead less
Containment and Reduction of Rework in Transport Mega Projects. Mega transport projects (>$1 billion) are poorly managed during their construction with significant cost and schedule overruns and benefit shortfalls regularly being experienced. Having to perform rework has been identified as a major factor that contributes to these unintended consequences. As there has been limited research that has empirically examined rework causation, an inability to develop effective rework containment and red ....Containment and Reduction of Rework in Transport Mega Projects. Mega transport projects (>$1 billion) are poorly managed during their construction with significant cost and schedule overruns and benefit shortfalls regularly being experienced. Having to perform rework has been identified as a major factor that contributes to these unintended consequences. As there has been limited research that has empirically examined rework causation, an inability to develop effective rework containment and reduction strategies prevails. This research aims to develop a theoretical model that can be used to develop robust containment and reduction strategies to mitigate the adverse economic, productivity and safety consequences that materialize from performing rework during the construction of mega transport projects.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100010
Funder
Australian Research Council
Funding Amount
$4,918,357.00
Summary
ARC Research Hub for Smart Next Generation Transport Pavements. The ARC Research Hub for Smart Next Generation Transport Pavements aims to make road, airport and dockyard pavements smart, low cost, long-lasting, safe, green and adaptable to future transport demands. Australia’s road network, upon which the nation depends for its economic and social prosperity, is at risk due to increases in passenger and freight load degradation of the road network, and material and expertise scarcity. The Hub w ....ARC Research Hub for Smart Next Generation Transport Pavements. The ARC Research Hub for Smart Next Generation Transport Pavements aims to make road, airport and dockyard pavements smart, low cost, long-lasting, safe, green and adaptable to future transport demands. Australia’s road network, upon which the nation depends for its economic and social prosperity, is at risk due to increases in passenger and freight load degradation of the road network, and material and expertise scarcity. The Hub will deliver new materials and modelling, smart construction, and rehabilitation systems required for future demands, while enhancing road safety and reducing environmental impact.
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Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information t ....Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information through computational intelligence. The expected outcome will be an intelligent asset management platform that provides structured and semantically enriched lifecycle asset information for optimised solutions to help reduce the cost, time and effort in asset information storage and retrieval, and decision-making. Read moreRead less