Michael Rigby

Michael Rigby
University of Melbourne | MSD · Faculty of Architecture, Building and Planning

BDes, BGeomE(Hons), PhD

About

22
Publications
6,624
Reads
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88
Citations
Introduction
Michael is a spatial scientist with a background in design and engineering, working at the Australian Urban Research Infrastructure Network (AURIN) based at The University of Melbourne. His current research interests include multidisciplinary eResearch, understanding users and geographic information science topics of representation, analysis, visualisation and decision making, with a keen eye on cybernetics and the social implications of technology.
Additional affiliations
May 2019 - present
University of Melbourne
Position
  • Subject Content Development
Description
  • Spatial Analytics
December 2018 - June 2019
University of Melbourne
Position
  • Managing Director
December 2018 - June 2019
University of Melbourne
Position
  • Managing Director
Education
August 2011 - November 2015
University of Melbourne
Field of study
  • Engineering
February 2004 - November 2007
February 2000 - November 2002

Publications

Publications (22)
Conference Paper
Analogies of the human body have been used for centuries to describe urban forms and are now being used to describe flows of resources and social interactions in cities and towns captured digitally through data. As the body has multiple systems, cities and towns can also be understood from this perspective with interdependent energy, transport and...
Presentation
Full-text available
While there has been significant effort in Australia and overseas to capture open spaces using a range of manual/automated techniques, differences in definition and representation between jurisdictions continue to hamper our ability to analyse and value open spaces in our cities and towns (Koohsari et al., 2015; Plant et al., 2017; Lamb et al., 201...
Conference Paper
Given increasing pressures from population growth and land use change, Australian researchers from academia and government require access to high value water and energy (WE) consumption data for planning and policy-making purposes. While recent data initiatives from the federal government have sought to unlock data, further work is needed to harmon...
Conference Paper
The Australian population census is now over 100 years old. The capacity to access, analyze and visualize census data is however highly problematic for Australian researchers. Spatial analysis in particular is limited, with digital boundaries for the Australian census dating back only to 1981, despite the existence of census boundary maps dating ba...
Conference Paper
Open spaces matter to Australian communities. Their benefits can be seen across various dimensions of society, such as spaces for improving health and well-being, positive impacts on economic performance through property uplift, and environmental benefits via improved air quality and increased biodiversity. While the value of open space data is cle...
Conference Paper
Full-text available
The monitoring and evaluation of Australia’s progress towards the Sustainable Development Goals (SDGs) requires access to relevant, high value geospatial data. The Australian Urban Research Infrastructure Network (AURIN) is a proven federally funded spatial data infrastructure (SDI) for research, which is well positioned to take on various dimensio...
Article
Full-text available
In the film Her, the main character Theodore sits in a darkened room, lit only by a computer screen in front of him. A synthetic voice helps him to set up his new Operating System. “Would you like your OS to have a male or female voice?” it asks. “Female, I guess,” says Theodore. “How would you describe your relationship with your mother?” asks the...
Poster
Assessment of the impact and societal benefit of Earth Observation (EO) is a multidisciplinary task that involves the social, economic and environmental knowledge to formulate indicators and methods. The value of information (VOI) of EO is based on case studies that document the value in use of the information in a specific decision. A case study i...
Chapter
A number of recent technological breakthroughs promise disrupting urban mobility as we know it. But anticipating such disruption requires valid predictions: disruption implies that predictions cannot simply be extrapolations from a current state. Predictions have to consider the social, economic and spatial context of mobility. This paper studies m...
Article
Full-text available
Interacting with ridesharing systems is a complex spatiotemporal task. Traditional approaches rely on the full disclosure of a client's trip information to perform ride matching. However during poor service conditions of low supply or high demand, this requirement may mean that a client cannot find any ride matching their intentions. To address thi...
Article
Interacting with ride-sharing systems for ad hoc travel is a complex spatio-temporal task. The dynamics of service supply and demand challenge the rigidity of traditional human–computer interfaces, introducing service uncertainty and creating a knowledge gap which hinders a client's travel planning. Such interface constraints may mean that a client...
Thesis
Full-text available
Existing ridesharing systems are too rigid for on-demand travel. Built from the perspective of classic, vehicle assignment algorithms in operations research and optimisation fields, their designs are highly prescriptive and rely on the full disclosure of trip information from both vehicle and client to perform ride matching. For a client user this...
Poster
The aim of this project is to explore the feasibility of a demand responsive transport mode in the urban transport fabric. This mode provides ad-hoc point-to-point transport, which includes serving the last mile problem: transport from and to mass transport hubs along with other intelligent navigation aspects. For more information log on to http://...
Article
Invasive populations are often irregularly distributed due to sporadic dispersal events and patchy distribution of suitable habitat, making it difficult to recognize the population boundary and effectively target management. We designed a survey prioritization that addresses these irregularities and tested it on an invasive King Devil Hawkweed (Hie...
Article
Full-text available
Interacting with an application for shared mobility is a complex spatio-temporal task, considering the degrees of freedom in planning and preferences together with the dynamics of supply. Traditional approaches also rely on the disclosure of inherently private, discrete information from both vehicle and client to perform ride matching. Catering for...
Conference Paper
Interacting with an application for shared mobility is a complex spatio-temporal task, considering the degrees of freedom in planning and preferences together with the dynamics of supply. Traditional approaches also rely on the disclosure of inherently private, discrete information from both vehicle and client to perform ride matching. Catering for...
Conference Paper
Interacting with dynamic ride sharing systems for ad-hoc travel is a complex spatio-temporal task. The uncertainty of service supply and demand in this constrained arena challenges the rigidity of traditional human-computer interfaces. Without knowledge of service potential or the effect of their own limiting constraints, clients may simply not fin...
Conference Paper
Full-text available
Existing ride sharing systems for commuting in urban environments are rigid. They rely on the communication of discrete, spatio-temporal constraints from both vehicle and client to perform ride-matching. From a client user perspective these approaches are problematic, leading to location-privacy issues and the use of additional communication channe...
Conference Paper
Full-text available
Travel planning in highly dynamic transportation networks, networks encountering events at any time, requires communication capabilities and planning flexibility from all travelling entities. In this paper we suggest and test a novel information dissemination strategy, which computes the relevance of pieces of information based on smart methods bor...

Network

Cited By

Projects

Projects (2)
Project
Existing ridesharing systems are too rigid for on-demand travel. Built from the perspective of classic, vehicle assignment algorithms in operations research and optimisation fields, their designs are highly prescriptive and rely on the full disclosure of trip information from both vehicle and client to perform ride matching. For a client user this approach becomes problematic, particularly during poor or uncertain service conditions, when they may not be able to find any ride matching their request. Critically, existing systems do not provide the client with adequate feedback to assist their travel planning, resulting in a significant knowledge gap that hinders the overall usability of the system. New players such as Uber and Lyft have tried to bridge this gap using visual map-based client user interfaces. Yet in retaining the classic, vehicle perspective they too encounter the same usability issue when they are unable to respond to requests by optimising or allocating vehicles due to real-time constraints such as demand or congestion. To account for these aspects this research leverages location-aware mobile devices and spatial information systems to develop a new approach for ridesharing. It inverts the classic vehicle perspective into a service representation to create a novel way to think about and use ridesharing systems, one which allows a client to respond to the system's current state however uncertain or heterogeneous it may be. It hypothesises that it is possible to design a representation of ridesharing service potential matching a client's request, which can be understood and used for travel planning purposes. This hypothesis is tested using an incremental approach, which builds from theory through design towards validation. First, it adapts and exploits concepts from quantitative time geography to create a discrete representation of ridesharing opportunity called launch pads. Second, it extends this model to create a continuous representation that fully communicates the system's potential. Third, it enhances both representations to incorporate additional ridesharing dimensions for decision making. Fourth, usability testing is performed in various simulated scenarios, providing early feedback on the proposed approach and identifies a set of future work towards validating the concept. This thesis presents novel contributions to improve the design of software applications for ridesharing. Its major results are the identification of a knowledge gap in existing systems and the design of an opportunistic approach that overcomes it. The key contributions include the launch pad concept based on time geography, methods to extend and enhance this representation with accurate ride attributes and the design of a novel 2-step negotiation for improved design making. Importantly the new approach facilitates client flexibility in both space and time for ridesharing and contributes towards improving the usability of intelligent shared ride systems using autonomous vehicles.
Project
Serving over 5000 spatial datasets from across Australia, AURIN is a research infrastructure that supports researchers and decision makers with data that is findable, accessible, interoperable and re-usable. For more information visit https://aurin.org.au/