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: 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
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
Promoting active travel and public transport for a post-pandemic world. In many major cities, COVID-19 stimulated the provision of open streets, pop up bike lanes and widened pedestrian access, prompting unprecedented increases cycling and walking. While this type of infrastructure has always been supported by urban planners and designers, the pandemic has served as a vital inflection point, enabling cities to pursue long-term sustainable transport initiatives, including investment in Active Tra ....Promoting active travel and public transport for a post-pandemic world. In many major cities, COVID-19 stimulated the provision of open streets, pop up bike lanes and widened pedestrian access, prompting unprecedented increases cycling and walking. While this type of infrastructure has always been supported by urban planners and designers, the pandemic has served as a vital inflection point, enabling cities to pursue long-term sustainable transport initiatives, including investment in Active Travel (AT). There is an opportunity to promote AT as part of an integrated transport strategy, and to develop tools for the robust evaluation of AT impacts to inform future investment strategies. This proposal will provide our partner organisation Transport for New South Wales (with the knowledge required to achieve this.
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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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