A systemic model to underpin enhanced management of powered-two-wheelers as part of a safe, sustainable transport system. Better management of motor scooters and motorbikes (Powered-2-wheelers or P2W) will deliver economic, environmental and social benefits. Road crashes involving P2Ws cost the Australian community in excess of $2 billion per annum. There are also the broader social impacts for crash victims, their families and communities from the potentially long-term pain, grief and debilitat ....A systemic model to underpin enhanced management of powered-two-wheelers as part of a safe, sustainable transport system. Better management of motor scooters and motorbikes (Powered-2-wheelers or P2W) will deliver economic, environmental and social benefits. Road crashes involving P2Ws cost the Australian community in excess of $2 billion per annum. There are also the broader social impacts for crash victims, their families and communities from the potentially long-term pain, grief and debilitating injuries. This project will provide insight into how the incidence and costs associated with P2W crashes can be reduced. In addition, congestion costs in each of Australia's capital cities are on the order of $3 billion per annum and there is potential for P2W research to reduce not only that cost but also the broader environmental impacts of travel by providing an alternative to cars.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100103
Funder
Australian Research Council
Funding Amount
$373,506.00
Summary
Understanding the automobility decisions of Australian millennials. The aim of this project is to understand the decision-making of young Australians regarding driver licensing and car travel. After decades of growth in car use, young adults are now becoming less likely to get a licence and drive cars. This reduction in car dependence provides an opportunity to reduce road deaths and injuries, road congestion and greenhouse gas emissions. Understanding how and why young adults make decisions abo ....Understanding the automobility decisions of Australian millennials. The aim of this project is to understand the decision-making of young Australians regarding driver licensing and car travel. After decades of growth in car use, young adults are now becoming less likely to get a licence and drive cars. This reduction in car dependence provides an opportunity to reduce road deaths and injuries, road congestion and greenhouse gas emissions. Understanding how and why young adults make decisions about their current and future car mobility could support this societal transformation and enhance sustainability and well-being.Read moreRead less
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
An innovative mechanism for optimising freeway traffic efficiency, safety, and sustainability via variable speed limit control. Congestion, safety, and emissions are three major traffic problems threatening the Australian economy. This project aims to develop a novel approach to collectively handle these problems for freeway traffic using variable speed limits (VSL). The project tasks address modelling, VSL controller design and automatic fine tuning of VSL controllers.
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
Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project inclu ....Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project include novel big data management and analytics techniques, and new edge computing models for vehicular networks. The success of this project should bring several key benefits including reducing greenhouse gas emissions on roads, facilitating urban planning, and improving road safety.Read moreRead less
Using visual science to reduce the dangers of night driving. This project aims to develop novel tests of visual function relevant to the modern night driving environment. Night driving is challenging for all drivers and has been linked to poor visibility under low light conditions. This project will characterise the visual challenges of the modern night driving environment, develop visual tests that incorporate the dynamic light levels typical of night-time roads and assess the association of th ....Using visual science to reduce the dangers of night driving. This project aims to develop novel tests of visual function relevant to the modern night driving environment. Night driving is challenging for all drivers and has been linked to poor visibility under low light conditions. This project will characterise the visual challenges of the modern night driving environment, develop visual tests that incorporate the dynamic light levels typical of night-time roads and assess the association of these tests with night driving performance. The outcomes will contribute new knowledge regarding dynamic visual processing and the ageing visual system and will inform vision testing, potential interventions to improve visual function for night driving and reduce the dangers of night driving.Read moreRead less
The Australian naturalistic driving study: innovation in road safety research and policy. A revolutionary new approach, the naturalistic driving study, will investigate what people actually do when they drive, in normal and safety-critical situations. It will provide Australia with answers to some intractable, high priority, road safety problems that cannot be answered using current methods, thereby saving hundreds of lives.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100050
Funder
Australian Research Council
Funding Amount
$570,000.00
Summary
Integrated facility for recording driver and road user behaviour. The integrated facility will be used to record and analyse data on driver and road user behaviour, in normal and safety-critical situations, for thousands of Australian drivers. The data yielded will be used to develop new and improved countermeasures for reducing road deaths and serious injuries on Australian roads.
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