Econometrics, land use inputs, and strategic transport models

The purpose of this project is to improve the interactions between urban transport and land use systems, especially at the level of individual decision makers (households and enterprises). It will approach this through the provision of advanced econometric support in a practical implementation of a bid-rent model structure and parameter estimation as part of a newly established land use model. This will produce robust and high-quality household and business activity inputs to transport modelling.

This is necessary to facilitate the understanding of impacts of new and emerging transport technologies and behaviour changes (including the effects of autonomous vehicles, shared vehicle ownership, shared car driving and ride-sharing, and voluntary household behavioural change), enabling the land use model to better estimate behavioural responses through the incorporation of location choices of households and business.

This research will contribute to providing an enhanced understanding of:

• the econometrics theory underlying the model
• estimating and using the bid function

Participants

• University of Western Australia
• Main Roads Western Australia
• Department of Transport (WA)
• Department of Planning Lands and Heritage Western Australia

Project background

The interaction between Transport and Land use systems has been recognised as a critical issue over the years (e.g. Hayashi and Roy 1996, US EPA 2000, Lautso et al 2004, Litman 2014), and is now a major constraint to the performance of both land use and transport models.

Research is needed to improve the understanding of the interactions between urban transport and land use systems, especially at the level of individual decision makers (households and enterprises), and for the development of enhanced analytical tools and models for describing the interactions and their impacts.

Land use and transport model interactions take place through activities (residential and business) and accessibility. Land use model outputs in the form of jobs and household activity patterns, feed into transport models. After transport models have calculated trips for different purposes, assigned them to mode and routes on the basis of the land use inputs, congestion and accessibility outputs are fed back to the land use model, influencing job and housing locations (Figure 1).

Figure 1: Example of interactions between a land use (Cube Land) and

transport (Cube Voyager) model within Citilan’s Cube platform

The focus of this project is on improving the land use model’s households and business activity inputs to transport modelling. In order to facilitate the understanding of impacts of new and emerging transport technologies and behaviour changes (including the effects of autonomous vehicles, shared vehicle ownership, shared car driving and ride-sharing, and voluntary household behavioural change), it is crucial that the land use model can estimate behavioural responses through the incorporation of location choices of households and business.

Land use models with a strong grounding in land market economic theory thus currently dominate international best practice. Available proprietary software such as Cube Land (Citilabs, 2015), thus consider behaviour responses to land rent, transport service changes, land demand and supply demand management, using econometrics methods, including random utility functions and bid rent theory. Random utility models or discrete choice models analyse individual behaviour under hypothetical choices with variable attributes while bid-rent models determine stochastic Willingness to Pay (WTP) functions of market agents.

Martinez (1996a) combined the bid-rent theory and discrete choice random utility theory into a bid-choice theory and developed an empirical application of an integrated transport and land use model comprising a bid-rent model called MUSSA and a transport model called ESTRAUS. The MUSSA model estimates land rents considering land availability and developer’s behaviour. Its outputs of locations of activities (households and firms) can feed ESTRAUS, ESTRAUS can then calculate trip frequencies by daily periods and trip purposes. ESTRAUS’s outputs of trip patterns and costs and impact on transport systems in turn provide measures of accessibility for MUSSA.

Recently, MUSSA was built into the internationally accepted industry standard Cube software system for transport analysis and modelling, where it is known as the Cube Land module. This enables direct interaction between Cube Land and Cube Voyager (Cube’s transport demand and network performance module) thus providing the opportunity for integrated transport and land use modelling within an established software platform (Citilabs 2015).

Western Australia’s Departments of Planning, Land and Heritage (DPLH) and Transport (DOT) are currently developing/testing modules for the integration of their strategic models in Cube Land and Voyager respectively. While DOT have been running Cube Voyager for some years, Cube Land is a recent acquisition for DPLH and they are still in the set-up phase. As part of this establishment phase, DPLH has identified the need for research support in relation to the econometrics underpinning of Cube Land.

The research will contribute to providing an enhanced understanding of:

• the econometrics theory underlying the model
• estimating and using the bid function, particularly in relation to Cube Land, is required to “shed light on many issues we have encountered in the setting up of Cube Land” (Dr Simon Zheng, Principal Economic Forecaster, DPLH).

This “look under the hood of Cube Land” will contribute to improvements in the quality of the activity estimates produced by Cube Land as input to the transport model, strengthening the interaction between the land use and transport models.

Overall, more accurate behavioural response estimation will be enabled resulting in an improved capacity to respond to complex policy questions and to offer efficient and sustainable urban planning and transport solutions for emergent socio-demographic changes (e.g., ageing, new alternatives for vehicle use, increased focus on active lifestyles and changes in housing preferences).

It has been argued that more comprehensive analysis of social, economic and environmental issues can only be undertaken (in the longer-term) using functional, integrated land use-transport models (Meng et al. 2015).

This project therefore contributes directly to the policy objectives to develop low-cost, reliable, resilient and efficient land use-transport systems that respond to Australia’s changing urban communities and assists businesses to meet their needs in terms of location and transport.

Project objectives

The project’s aim is to improve the households and business land use activity inputs to transport modelling provided by a spatial econometric land use model, with particular focus on the proprietary software application in use in Perth and Peel, WA.

This will be achieved through the provision of an advanced and customised understanding of the econometrics underpinnings and the use and estimation of the bid-rent function, in order to improve the quality and context-specific applicability of the land use model outputs of residential and business activities.

The project objectives are to:

• Provide an enhanced ‘under the hood’ understanding of advanced econometrics as applied in practice in spatial econometrics land use models with particular emphasis on Cube Land as applied in Perth and Peel, WA; and
• Capture and share the learning from a review of the application and use of the bid-rent model structure and parameter estimation elsewhere in the world in order to provide recommendations for enhancing the implementation of the Perth and Peel Cube Land model, given available data and software limitations.

References

• Citilabs (2020) CUBE – Transportation and Land-Use Modeling, available at https://www.citilabs.com/software/cube/, Mountain View, California, USA.
• Hayashi, Y. and Roy, J.R. (eds.) (1996) Transport, Land-use and the Environment, Kluwer Academic Publisher, Dordrecht.
  US EPA (2000) Projecting Land-Use Change: A Summary of Models for Assessing the Effects of Community Growth and Change on Land-Use Patterns. EPA/600/R-00/098, ISBN-13: 978-1493745111.
• Lautso, K., Spiekermann, K,, Wegener, M., Sheppard, I., Steadman, P., Martino, A., Domingo, R. and Gayda, S. (2004) PROPOLIS: Planning and Research of Policies for Land Use and Transport for Increasing Urban Sustainability, Report to the European Commission under the Energy, Environment and Sustainable Development Thematic Programme of the Fifth RTD Framework Programme, contract no EVK4-1999-00005, available at http://www.spiekermann-wegener.de/pro/pdf/PROPOLIS_Final_Report.pdf.
• Litman, T. and Steele, R. (2014) Land use impacts on transport: how land use factors affect travel behaviour, Victoria Transport Policy Institute, Victoria BC, www.vti.org.
  Martínez, F.J. (1996a) MUSSA: Land Use Model for Santiago City, Transportation Research Record, 1552(1), 126-134.
• Martinez, F.J. (1996b) Analysis of urban environmental policies assisted by behavioural modelling. In Hayashi, Y. and Roy, J.R. (eds) Transport, Land-Use and the Environment, Kluwer Academic Publishers, Dordrecht, 233-257.
• Meng, L., Taylor, M.A.P., and Scrafton, D. (2016) Combining Latent Class Models and GIS Models for Integrated Transport and Land Use Planning – A Case Study Application, Urban Policy and Research, 1-25.