Discovery Early Career Researcher Award - Grant ID: DE130100205
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Optimisation of transit priority in a transportation network. This project is aimed at developing an optimised approach to combine various types of public transport priority in an urban network which can be used by transport planners to increase the efficiency of traffic movements and reduce traffic congestion. The case study is the network of Brisbane including all arterial and local roads.
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
Funding on the line: public transport financing and property value capture. This project aims to develop property value capture schemes that would provide alternative funding for public transport infrastructure. It plans to model the timing and spatial patterns of property value uplift from recent investments in rail, busways and ferries in Queensland and New South Wales. It then intends to conduct a survey of Australian stakeholders and discrete choice modelling to determine willingness-to-pay. ....Funding on the line: public transport financing and property value capture. This project aims to develop property value capture schemes that would provide alternative funding for public transport infrastructure. It plans to model the timing and spatial patterns of property value uplift from recent investments in rail, busways and ferries in Queensland and New South Wales. It then intends to conduct a survey of Australian stakeholders and discrete choice modelling to determine willingness-to-pay. This data is then expected to be used to develop an institutionally, legally and politically feasible scheme for implementation in Australia, focused on cases including extension to the Gold Coast light rail network.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
Understanding impact of autonomous vehicles on behaviour and interactions. Understanding impact of autonomous vehicles on behaviour and interactions. This project aims to explore three human factor issues critical to the successful deployment of automated vehicles: factors influencing driver choice of automated vehicle control; interactions between automated and manually controlled vehicles; and driver detection, recognition, and reaction to automated vehicle system failures. Automated vehicles ....Understanding impact of autonomous vehicles on behaviour and interactions. Understanding impact of autonomous vehicles on behaviour and interactions. This project aims to explore three human factor issues critical to the successful deployment of automated vehicles: factors influencing driver choice of automated vehicle control; interactions between automated and manually controlled vehicles; and driver detection, recognition, and reaction to automated vehicle system failures. Automated vehicles are predicted to be transformative, but their ultimate success and expected societal benefits will depend on drivers’ trust in them and on how people choose to use and interact with them. Insights from this research should prepare our society for more automated vehicles on the roadways.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101320
Funder
Australian Research Council
Funding Amount
$425,970.00
Summary
Rethinking traffic modelling for next generation city-scale networks. This project aims to develop an efficient traffic simulation model that enables data-informed traffic monitoring and automated model development, streamlining the fundamental transformation that next-generation cities will undergo in the coming decades. The project expects to generate new knowledge in traffic modelling by developing an innovative approach to inferring traffic conditions and traveller behaviour from diverse dat ....Rethinking traffic modelling for next generation city-scale networks. This project aims to develop an efficient traffic simulation model that enables data-informed traffic monitoring and automated model development, streamlining the fundamental transformation that next-generation cities will undergo in the coming decades. The project expects to generate new knowledge in traffic modelling by developing an innovative approach to inferring traffic conditions and traveller behaviour from diverse data feeds, and automating model calibration through an optimisation formulation. Expected outcomes address the eventual transition to smart cities and connected and autonomous vehicle technologies, providing significant social, economic and environmental benefits through optimal planning and effective operation schemes.Read moreRead less
Assessing the full impacts of high efficiency heavy vehicles in urban traffic networks using new analytical tools. Significant economic benefits result from new innovative heavy vehicles, which are able to carry up to twice the payload of standard semi-trailers. In addition, those vehicles have the potential to reduce overall accidents and evironmental degradation. Those benefits need to be traded-off against the impacts on other road users. This research will improve the operation of such ve ....Assessing the full impacts of high efficiency heavy vehicles in urban traffic networks using new analytical tools. Significant economic benefits result from new innovative heavy vehicles, which are able to carry up to twice the payload of standard semi-trailers. In addition, those vehicles have the potential to reduce overall accidents and evironmental degradation. Those benefits need to be traded-off against the impacts on other road users. This research will improve the operation of such vehicles in regional centres by producing: (1) an assessment methodology to deal with options for network efficiency gains which will capture the full impacts; and (2) a computer modelling tool based on fundamental research to quantify those impacts, in terms of delays and accident rates.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100449
Funder
Australian Research Council
Funding Amount
$336,000.00
Summary
Modelling mixed traffic of traditional, connected, and automated vehicles. This project plans to address the challenge of efficiently operating mixed traffic flow of traditional, connected and automated vehicles. The rapid advancement of technologies is currently turning connected and automated vehicles from science fiction into science fact. However, there are no existing traffic flow models capable of reproducing features of mixed traffic flow consisting of traditional, connected and automated ....Modelling mixed traffic of traditional, connected, and automated vehicles. This project plans to address the challenge of efficiently operating mixed traffic flow of traditional, connected and automated vehicles. The rapid advancement of technologies is currently turning connected and automated vehicles from science fiction into science fact. However, there are no existing traffic flow models capable of reproducing features of mixed traffic flow consisting of traditional, connected and automated vehicles. This project aims to address this knowledge deficit and develop an analytical tool able to accurately model mixed traffic flow. This new knowledge and model are prerequisites to effective operation and control of traffic flow of traditional, connected and automated vehicles.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190101020
Funder
Australian Research Council
Funding Amount
$357,000.00
Summary
Data-driven simulation of large traffic networks using trajectory data. This project aims to develop a low-cost, data-driven framework that builds a traffic simulation model automatically and directly from vehicle trajectory data to enable rapid and reliable analysis of large-scale traffic networks. The project expects to generate new knowledge in the area of transport engineering using an innovative approach to inferring travel behaviours, movement patterns and traffic dynamics from increasingl ....Data-driven simulation of large traffic networks using trajectory data. This project aims to develop a low-cost, data-driven framework that builds a traffic simulation model automatically and directly from vehicle trajectory data to enable rapid and reliable analysis of large-scale traffic networks. The project expects to generate new knowledge in the area of transport engineering using an innovative approach to inferring travel behaviours, movement patterns and traffic dynamics from increasingly available urban trajectory data. Expected outcomes include improved decision support for urban planners and traffic operators and enhanced traffic management and incident response capabilities, providing significant social, economic and environment benefits through optimised road use and urban flow.Read moreRead less