Integrating Attribute Decision Heuristics into Travel Choice Models that accommodate Risk Attitude and Perceptual Conditioning. This proposal has the specific objective of integrating two disconnected literatures that are having a major influence on the behavioural and statistical performance of discrete choice models in travel choice modelling. These fields are attribute processing strategies and the conditioning of the marginal utility of attributes by risk attitude and perceptual conditioning ....Integrating Attribute Decision Heuristics into Travel Choice Models that accommodate Risk Attitude and Perceptual Conditioning. This proposal has the specific objective of integrating two disconnected literatures that are having a major influence on the behavioural and statistical performance of discrete choice models in travel choice modelling. These fields are attribute processing strategies and the conditioning of the marginal utility of attributes by risk attitude and perceptual conditioning. These two major developments have not been jointly integrated into a behaviourally richer representation of choice making. Given the encouraging evidence from both literatures, the research will determine more precisely the benefits in terms of improved estimates of willingness to pay for specific attributes and also increased predictive power. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101793
Funder
Australian Research Council
Funding Amount
$423,038.00
Summary
Quantifying and managing the network impacts of transport sharing services. This project aims to address the challenge of effectively modelling multiple transport sharing services (e.g., ridesharing and parking sharing) in a multimodal network, and efficiently operating these services, and incentivising people to use them. The project expects to generate new knowledge in shared transport by developing an innovative approach to systematically reproducing and optimising network impacts of sharing ....Quantifying and managing the network impacts of transport sharing services. This project aims to address the challenge of effectively modelling multiple transport sharing services (e.g., ridesharing and parking sharing) in a multimodal network, and efficiently operating these services, and incentivising people to use them. The project expects to generate new knowledge in shared transport by developing an innovative approach to systematically reproducing and optimising network impacts of sharing services on travel choices, sharing demand-supply matching patterns, movement trajectory features and traffic dynamics. Expected outcomes include new models and strategies to improve decision support for transport planners and operators. This should provide significant benefits for human mobility and city sustainability.Read moreRead less
Integrating network modelling with observed choice data for multi-criteria optimisation of complex car share systems: cost, mobility and transit usage. This project will develop methods to determine an efficient car share system, which includes optimal location, one-way car sharing, and how carshare influences the broader transport system. By adopting such new comprehensive methods, the overall transport system will benefit through potential improvements in public transit usage.
Innovative urban traffic congestion solutions: optimising road space using networks of multi-class priority lanes. This project strengthens national approaches to a pervasive Australian problem; growing traffic congestion deteriorating liveability, environmental health and economic performance of the cities. This project improves approaches for traffic priority design to improve the efficiency of several class of vehicles and therefore, reducing traffic congestion.
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: DE210100602
Funder
Australian Research Council
Funding Amount
$424,000.00
Summary
Market Design of Next Generation of Shared and Automated Transport Services. This project aims to develop novel quantitative models and market design methods to fundamentally transform the analysis, control and regulation of shared and automated point-to-point transport services in multimodal networks. The project offers an innovative non-equilibrium approach that models multiple competitive transport platforms, travellers, freelancer drivers and transport legislator entity to ensure achieving s ....Market Design of Next Generation of Shared and Automated Transport Services. This project aims to develop novel quantitative models and market design methods to fundamentally transform the analysis, control and regulation of shared and automated point-to-point transport services in multimodal networks. The project offers an innovative non-equilibrium approach that models multiple competitive transport platforms, travellers, freelancer drivers and transport legislator entity to ensure achieving social welfare. The project outcomes address the eventual transition towards automation where platforms own and utilise different proportions of AVs in their fleet. The project expects to generate new knowledge of transport science that can be used to lessen social, economic and environmental impacts of private car ownership.
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Business location decisions. This project aims to develop a forecasting model system for economic planning that integrates business (re-) location and co-location choices. Improved transport infrastructure connects places and can influence the location of businesses. This project will use forecasting models to quantify the drivers of firm location decisions linked to an integrated strategic transport and land use modelling system. This project expects to provide guidance for transport investment ....Business location decisions. This project aims to develop a forecasting model system for economic planning that integrates business (re-) location and co-location choices. Improved transport infrastructure connects places and can influence the location of businesses. This project will use forecasting models to quantify the drivers of firm location decisions linked to an integrated strategic transport and land use modelling system. This project expects to provide guidance for transport investment that brings gains in productivity to industry and the economy and wellbeing to individuals and society.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100113
Funder
Australian Research Council
Funding Amount
$390,000.00
Summary
Travel Choice Simulation Laboratory (TRACSLab): a visualisation laboratory to study travel behaviour and drivers’ interactions. Travel Choice Simulation Laboratory (TRACSLab) is a world-first facility to observe collective travel choice in a realistic lab environment. It is unique due to the focus on travel choice, networked interaction and strong teaming. The findings of the lab will support a new generation of transport analysis techniques for emerging issues such as sustainability, reliabili ....Travel Choice Simulation Laboratory (TRACSLab): a visualisation laboratory to study travel behaviour and drivers’ interactions. Travel Choice Simulation Laboratory (TRACSLab) is a world-first facility to observe collective travel choice in a realistic lab environment. It is unique due to the focus on travel choice, networked interaction and strong teaming. The findings of the lab will support a new generation of transport analysis techniques for emerging issues such as sustainability, reliability, and intelligent transport systems (ITS).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