Proactive detection of motor vehicle crash black spots based on their underlying behavioural, engineering, and spatially related causes. Road traffic crashes are responsible for about 1400 fatalities and 32,500 injuries on Australian roadways each year. A significant research opportunity exists to fundamentally rethink how the profession quantitatively identifies black spots on the transport network. The first project aim is to develop, test, and validate an evidence based methodology to proacti ....Proactive detection of motor vehicle crash black spots based on their underlying behavioural, engineering, and spatially related causes. Road traffic crashes are responsible for about 1400 fatalities and 32,500 injuries on Australian roadways each year. A significant research opportunity exists to fundamentally rethink how the profession quantitatively identifies black spots on the transport network. The first project aim is to develop, test, and validate an evidence based methodology to proactively detect motor vehicle crash black spots. The second aim is decompose (statistically) observed crashes at a site into their engineering, behavioural, and unobserved spatial components. The new methods combined will lead to fundamentally novel insights and knowledge regarding transport network safety management, in turn leading to reductions in the Australian road toll.Read moreRead less
Reducing aggression on our roads: testing a comprehensive model of aggressive driving. This project aims to increase our understanding of driver aggression, its causes and how it can be prevented. This will inform development of more effective educational and enforcement measures to reduce driver aggression and resultant road crashes, which have significant social and economic impacts on the Australian community.
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.
Application of contemporary systems-based methods to reduce trauma at rail level crossings. Crashes at railway level crossings continue to cause significant trauma across Australia. Despite being a longstanding safety problem, the design and operation of level crossings has not changed considerably for decades. This research will provide an in-depth understanding of road user, environmental and infrastructure-related factors that influence safety and performance at rail level crossings. This wil ....Application of contemporary systems-based methods to reduce trauma at rail level crossings. Crashes at railway level crossings continue to cause significant trauma across Australia. Despite being a longstanding safety problem, the design and operation of level crossings has not changed considerably for decades. This research will provide an in-depth understanding of road user, environmental and infrastructure-related factors that influence safety and performance at rail level crossings. This will be used to develop a world-first model of the level crossing system that is needed to support the development of innovative countermeasures that will improve safety. Reductions in the levels of significant trauma at level crossings, and new public policy for level crossing upgrades, are the intended real-world outcomes.Read moreRead less
Intention-aware cooperative driving behaviour model for Automated Vehicles. This project aims to investigate humans' cooperation with automated systems by conceptualising joint intention awareness. This project expects to generate knowledge about a new cooperative driving behaviour model for automated vehicles, utilising a transdisciplinary approach that mixes human-centric methods with deep learning techniques. Intended outcomes are new joint intention awareness theory, new interface for automa ....Intention-aware cooperative driving behaviour model for Automated Vehicles. This project aims to investigate humans' cooperation with automated systems by conceptualising joint intention awareness. This project expects to generate knowledge about a new cooperative driving behaviour model for automated vehicles, utilising a transdisciplinary approach that mixes human-centric methods with deep learning techniques. Intended outcomes are new joint intention awareness theory, new interface for automated vehicles, new methodology for cooperative behaviour research, and enhanced research capacity. The expected significant benefits are for automated systems to become more predictable, acceptable, readable and safer to use by everyday people.Read moreRead less
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
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
Discovery Early Career Researcher Award - Grant ID: DE200101079
Funder
Australian Research Council
Funding Amount
$426,241.00
Summary
Safe distractions? Taking the danger out of competing activities. Distracted driving is an increasing safety concern in Australia and worldwide. Smartphones play key roles in today’s professional and social contexts and current road safety policies based on stopping their use while driving have shown little success. Distraction is predicted to be an even greater issue in new semi-automated vehicles. This project proposes an innovative approach that will enable safe engagement in competing tasks ....Safe distractions? Taking the danger out of competing activities. Distracted driving is an increasing safety concern in Australia and worldwide. Smartphones play key roles in today’s professional and social contexts and current road safety policies based on stopping their use while driving have shown little success. Distraction is predicted to be an even greater issue in new semi-automated vehicles. This project proposes an innovative approach that will enable safe engagement in competing tasks while driving non-automated and semi-automated vehicles. The outcomes will underpin the development of new technologies to reduce the potential adverse effects of these distractions and thus reduce deaths and serious injuries, representing significant cost savings to the health system and the community.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180101449
Funder
Australian Research Council
Funding Amount
$361,996.00
Summary
Human factors approaches for the safe introduction of autonomous vehicles. This project aims to address potential safety risks arising from the introduction of advanced autonomous vehicles through a novel integration of human factors and computer-based simulation techniques. While automation promises to reduce crashes, the project expects to generate new knowledge about the emergence of risks through interactions between human road users and autonomous vehicles, particularly in the initial trans ....Human factors approaches for the safe introduction of autonomous vehicles. This project aims to address potential safety risks arising from the introduction of advanced autonomous vehicles through a novel integration of human factors and computer-based simulation techniques. While automation promises to reduce crashes, the project expects to generate new knowledge about the emergence of risks through interactions between human road users and autonomous vehicles, particularly in the initial transition period. The expected outcomes include an enhanced capacity to understand how risks emerge in complex systems, and the development of specific policy and regulatory interventions. The project expects to provide significant safety benefits by preventing new types of road crash events.Read moreRead less