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 real-time traffic signal system for safe and efficient intersections . Road traffic crashes result in 1,200 fatalities and another 36,500 injuries on Australian roads each year. Signalised intersections represent a high-risk node in a transportation network, but the current signal designs only consider efficiency but not safety. This project aims to unleash the power of artificial intelligence (AI) and integrate with the advanced extreme value models for proactive and efficient detection of cr ....A real-time traffic signal system for safe and efficient intersections . Road traffic crashes result in 1,200 fatalities and another 36,500 injuries on Australian roads each year. Signalised intersections represent a high-risk node in a transportation network, but the current signal designs only consider efficiency but not safety. This project aims to unleash the power of artificial intelligence (AI) and integrate with the advanced extreme value models for proactive and efficient detection of crash risk in real-time. Its innovations lie on developing a novel traffic signal control system balancing safety and efficiency of signalised intersections. The proposed real-time traffic signal system will fundamentally transform the intersection operation and lead to reductions of road fatalities, injuries and emissions.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
The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the ....The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the dangers to riders and pedestrians. This knowledge is expected to inform governments at all levels, industry and riders on how to optimise e-scooter design, use and regulation to contribute to improvements in transport, health and environmental outcomes for all Australians.Read moreRead less
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 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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Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less
Innovative Magnetorheological Powertrains for Electric Heavy Duty Vehicles. An electric vehicle powertrain mainly consists of an electric motor-driven system, a mechanical transmission and other components. This project aims to explore innovative powertrains with a regenerative braking function to maximise driving range, reduce power consumption, and enhance the dynamic performance of electrified vehicles. The proposed powertrains are expected to achieve seamless gear changing for driving and be ....Innovative Magnetorheological Powertrains for Electric Heavy Duty Vehicles. An electric vehicle powertrain mainly consists of an electric motor-driven system, a mechanical transmission and other components. This project aims to explore innovative powertrains with a regenerative braking function to maximise driving range, reduce power consumption, and enhance the dynamic performance of electrified vehicles. The proposed powertrains are expected to achieve seamless gear changing for driving and better braking performance by applying magnetorheological technology for a high-quality control of power-shifting, and therefore significantly improve vehicle dynamic and economic performance. A new era of high-efficiency electric powertrains could potentially be launched through the development of these novel technologies.Read moreRead less
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