A novel integrated motorway management system for less congested, more reliable and safer motorways. Motorway traffic congestion poses major economic, social and safety problems, which this project seeks to address through intelligent traffic management solutions as an alternative to massive infrastructure expansion. The project’s innovative traffic analysis and control system will reduce periods of congestion and increase driver safety.
Unifying Traffic Modelling and Safety Management for Safer and Faster Roads. This project aims to balance road safety and efficiency as conflicting goals of transport systems mixed with connected and automated vehicles (CAVs). This project is expected to generate fundamental knowledge on operational algorithms and analytics for CAVs and develop innovative tools for operating them. Expected outcomes include ground-breaking models capable of the co-estimation of efficiency and safety impacts of CA ....Unifying Traffic Modelling and Safety Management for Safer and Faster Roads. This project aims to balance road safety and efficiency as conflicting goals of transport systems mixed with connected and automated vehicles (CAVs). This project is expected to generate fundamental knowledge on operational algorithms and analytics for CAVs and develop innovative tools for operating them. Expected outcomes include ground-breaking models capable of the co-estimation of efficiency and safety impacts of CAVs, and control strategies to safely and efficiently integrate CAVs into existing transport systems. This should provide significant safety and efficiency benefits that currently cost about 1160 lives and 1.25 billion hours of congestion per year, and make Australia better prepared for the connected and automated vehicle era.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
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
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
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
Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to deve ....Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to develop unsupervised learning algorithms to infer high-level driver behaviours, intent and contextual information to automatically evaluate levels of risk under complex driving scenarios. It plans to validate the results using naturalistic driving datasets taken in large-scale deployments around the world. This innovation may improve automotive safety and facilitate the deployment of autonomous vehicles.Read moreRead less
Road safety and Aboriginal people. This study will involve an in-depth examination of factors underlying the high involvement in road crashes by Aboriginal people in Australia. Using mixed methods in six communities across NSW and South Australia it will inform development of new programs aimed at closing the gap in this important area.
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
Improving young drivers' speed management behaviour. This project incorporates proven educational and training techniques employed within the aviation industry to improve young drivers' speed management skills. Ultimately the results of this project will aid road safety authorities in redesigning training programmes to achieve this goal.