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
Electromagnetically Interconnected Suspension for Electrified Vehicles . This project aims to develop an innovative, electromagnetically interconnected suspension system to enhance vehicle ride comfort, stability and handling dynamics, and thus safety of electrified vehicles. Specifically, the project integrates a set of novel electromagnetic shock absorbers to form an effective electrical network so as to realise an electromagnetically interconnected suspension system. Advanced integrated con ....Electromagnetically Interconnected Suspension for Electrified Vehicles . This project aims to develop an innovative, electromagnetically interconnected suspension system to enhance vehicle ride comfort, stability and handling dynamics, and thus safety of electrified vehicles. Specifically, the project integrates a set of novel electromagnetic shock absorbers to form an effective electrical network so as to realise an electromagnetically interconnected suspension system. Advanced integrated control techniques can then be applied to improve vehicle performance and dynamics in three planes. The project will assist the rapid development of transportation electrification. The outcomes from this project will lead to tangible improvements in vehicle comfort and safety.Read moreRead less
Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely ....Condition Monitoring of Aircraft Propulsion for Automated Diagnostics. The integrity of the steering system is crucial for the safe operation of autonomous vehicles. This project aims at developing a new condition monitoring system able to diagnose steering faults earlier, provide a root-cause-analysis of malfunctions, and estimate associated failure risks in the future. The outcomes of this project will be a better understanding of steering faults and their effect on autonomous driving, timely diagnostics and prognostics and innovative proactive control measures that mitigate their impact on autonomous driving quality and safety. The expected benefits for the automotive industry and end-users include increased safety and reliability of steering systems, and higher confidence in autonomous driving.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
Improving novice drivers' speed and hazard management. The aim of the study is to extend the evidence-based approach we have developed for speed management (cognitive integration speed management training) to hazard management, thereby developing cognitive integration hazard management training for young drivers. Hence, this study is specifically designed to curb the alarming trend in young driver fatalities on Australian roads. The results of the research will provide clear direction to road au ....Improving novice drivers' speed and hazard management. The aim of the study is to extend the evidence-based approach we have developed for speed management (cognitive integration speed management training) to hazard management, thereby developing cognitive integration hazard management training for young drivers. Hence, this study is specifically designed to curb the alarming trend in young driver fatalities on Australian roads. The results of the research will provide clear direction to road authorities and driver training providers as to effective training strategies to improve young driver training, and ultimately improve road safety with this vulnerable population.Read moreRead less
Towards equity in crash protection. Women are at increased relative risk for death and serious injury in motor vehicle crashes compared to men and the reasons for this are not clear. This Fellowship aims to build a new model that describes the mechanistic pathways for this inequity to identify where and how intervention could reduce this relative risk. This will establish what population groups have good and poor access to the best vehicle safety technologies, the differences, and what might cau ....Towards equity in crash protection. Women are at increased relative risk for death and serious injury in motor vehicle crashes compared to men and the reasons for this are not clear. This Fellowship aims to build a new model that describes the mechanistic pathways for this inequity to identify where and how intervention could reduce this relative risk. This will establish what population groups have good and poor access to the best vehicle safety technologies, the differences, and what might cause these differences in the benefits of vehicle safety technology between women and men. The outcomes will be of use to academics, policy makers and industry designing to new ways to protect women in crashes and close this gender gap.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
Crashworthiness topology optimisation for light-weight battery compartments. This project uses computational modelling and optimisation methods to the design of battery compartments for electric vehicles. As the use of electric vehicles becomes more extensive, awareness of the consequences of catastrophic failure of high energy battery in a crash has increased. This project will develop novel design methodologies, using multi-disciplinary techniques for battery compartment structure. The methodo ....Crashworthiness topology optimisation for light-weight battery compartments. This project uses computational modelling and optimisation methods to the design of battery compartments for electric vehicles. As the use of electric vehicles becomes more extensive, awareness of the consequences of catastrophic failure of high energy battery in a crash has increased. This project will develop novel design methodologies, using multi-disciplinary techniques for battery compartment structure. The methodology will expand conventional crashworthiness design to the coupled mechanical-electrochemical-thermal problems. The proposed crashworthiness optimisation of battery compartment structure will enhance safety and reliability of electric vehicles, potentially benefiting consumers and manufacturers.Read moreRead less