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Accessibility Futures

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Abstract

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures on the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. A zone to zone travel time matrix was computed using SUE assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each TAZ within specified time ranges. Tables of person- weighed accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. The person-weighted accessibility results were then used to evaluate the planning scenarios. The results show that centralized population and employment produce the highest accessibility across all networks.

Suggested Citation

  • Paul Anderson & David Levinson & Pavithra Parthasarathi, 2011. "Accessibility Futures," Working Papers 000088, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:accessibilityfutures
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    File URL: http://hdl.handle.net/11299/180046
    File Function: Second version, 2014
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    References listed on IDEAS

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    1. David Levinson, 1998. "Accessibility and the Journey to Work," Working Papers 199802, University of Minnesota: Nexus Research Group.
    2. Leurent, Fabien M., 1997. "Curbing the computational difficulty of the logit equilibrium assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 31(4), pages 315-326, August.
    3. David Levinson & Ajay Kumar, 1995. "A Multi-modal Trip Distribution Model," Working Papers 199503, University of Minnesota: Nexus Research Group.
    4. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    5. David Levinson & Bernadette Marion, 2010. "The City is Flatter: Changing Patterns of Job and Labor Access in Minneapolis-Saint Paul, 1995-2005," Working Papers 000077, University of Minnesota: Nexus Research Group.
    6. Arthur Huang & David Levinson, 2011. "Non-work Vehicle Trip Generation from Multi- week In-vehicle GPS Data," Working Papers 000095, University of Minnesota: Nexus Research Group.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Pavithra Parthasarathi & David Levinson, 2010. "Network Structure and Metropolitan Mobility," Working Papers 000083, University of Minnesota: Nexus Research Group.
    2. David Levinson & Arthur Huang, 2012. "A Positive Theory of Network Connectivity," Environment and Planning B, , vol. 39(2), pages 308-325, April.
    3. Manaugh, Kevin & El-Geneidy, Ahmed, 2012. "What makes travel 'local': Defining and understanding local travel behaviour," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 15-27.
    4. Gibbons, Stephen & Lyytikäinen, Teemu & Overman, Henry G. & Sanchis-Guarner, Rosa, 2019. "New road infrastructure: The effects on firms," Journal of Urban Economics, Elsevier, vol. 110(C), pages 35-50.
    5. Ahmed El-Geneidy & David Levinson, 2011. "Place Rank: Valuing Spatial Interactions," Networks and Spatial Economics, Springer, vol. 11(4), pages 643-659, December.
    6. Mondschein, Andrew & Taylor, Brian D. & Brumbaugh, Stephen, 2011. "Congestion and Accessibility: What's the Relationship," University of California Transportation Center, Working Papers qt6bh2n9wx, University of California Transportation Center.
    7. Frank Primerano & Michael Taylor & Ladda Pitaksringkarn & Peter Tisato, 2008. "Defining and understanding trip chaining behaviour," Transportation, Springer, vol. 35(1), pages 55-72, January.
    8. Mondschein, Andrew & Taylor, Brian D & Brumbaugh, Stephen, 2010. "Congestion And Accessibility: What’S The Relationship?," University of California Transportation Center, Working Papers qt8135b0jh, University of California Transportation Center.
    9. Ahmed El-Geneidy & David Levinson, 2007. "Mapping Accessibility Over Time," Working Papers 200709, University of Minnesota: Nexus Research Group.
    10. Feng Xie & David Levinson, 2009. "Jurisdictional Control and Network Growth," Networks and Spatial Economics, Springer, vol. 9(3), pages 459-483, September.
    11. Rosa Sanchis-Guarner, 2012. "Driving Up Wages: The Effects of Road Construction in Great Britain," SERC Discussion Papers 0120, Centre for Economic Performance, LSE.
    12. Zhu, Weihua, 2009. "Design and Development of Novel Routing Methodologies for Dynamic Roadway Navigation Systems," University of California Transportation Center, Working Papers qt8d72371n, University of California Transportation Center.

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    More about this item

    Keywords

    Accessibility; Forecasting; Travel Demand; Scenarios; Trends; Transportation; Land Use.;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations
    • R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock
    • H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government

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