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
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
Design of micro-decisions in automated transport. This project aims to design methods and market algorithms for vehicle control to tackle traffic congestion with interactive micro-auctions, micro-tolling and cooperative games. Specifically, this project develops and designs incentives, auctions and behavioural and pricing rules to manipulate micro traffic dynamics such as lane-changing, merging, energy-efficient driving, and driving at intersections, in roads without defined lanes and shared spa ....Design of micro-decisions in automated transport. This project aims to design methods and market algorithms for vehicle control to tackle traffic congestion with interactive micro-auctions, micro-tolling and cooperative games. Specifically, this project develops and designs incentives, auctions and behavioural and pricing rules to manipulate micro traffic dynamics such as lane-changing, merging, energy-efficient driving, and driving at intersections, in roads without defined lanes and shared spaces to achieve collective macro benefits. The project targets mixed traffic where AVs and conventional human-driven vehicles interact and share the road. The project expects to generate new knowledge of transport science to lessen social, economic and environmental impacts of private cars.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
The effects of cyclic loading on partially saturated soils. This project aims to predict the settlement and strength of the upper, partially saturated layer of the ground when it is subjected to cyclic loading. Most of our critical infrastructure is built on or in this layer, but currently we cannot reliably predict the ground response of partially saturated soils to the cyclic loads that arise from earthquakes, traffic and construction processes. The project is expected to develop a new numeric ....The effects of cyclic loading on partially saturated soils. This project aims to predict the settlement and strength of the upper, partially saturated layer of the ground when it is subjected to cyclic loading. Most of our critical infrastructure is built on or in this layer, but currently we cannot reliably predict the ground response of partially saturated soils to the cyclic loads that arise from earthquakes, traffic and construction processes. The project is expected to develop a new numerical model that can predict the effects of cyclic loads, and provide updated engineering guidance to ensure the integrity of infrastructure dependent on partially-saturated soils. Improved predictions of the processes involved resulting from this project will have significant economic benefits, as well as ensuring the safety and security of infrastructure and reduced maintenance costs.Read moreRead less