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Accessibility and Centrality Based Estimation of Urban Pedestrian Activity

Author

Listed:
  • Brendan Murphy
  • David Levinson
  • Andrew Owen

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

Abstract

Non-motorized transportation, particularly including walking and bicycling, are increasingly becoming important modes in modern cities, for reasons including individual and societal wellness, avoiding negative environmental impacts of other modes, and resource availability. Institutions governing development and management of urban areas are increasingly keen to include walking and bicycling in urban planning and engineering; however, proper placement of improvements and treatments depends on the availability of good usage data. This study attempts to predict pedestrian activity at 1123 intersections in the Midwestern, US city of Minneapolis, Minnesota, using scalable and transferable predictive variables such as economic accessibility by sector, betweenness network centrality, and automobile traffic levels. Accessibility to jobs by walking and transit, automobile traffic, and accessibility to certain economic job categories (Education, Finance) were found to be significant predictors of increased pedestrian traffic, while accessibility to other economic job categories (Management, Utilities) were found to be significant predictors of decreased pedestrian traffic. Betweenness centrality was not found to be a significant predictor of pedestrian traffic, however the specific calculation methodology can be further tailored to reflect real-world pedestrian use-cases in urban areas. Accessibility-based analysis may provide city planners and engineers with an additional tool to predict pedestrian and bicycle traffic where counts may be difficult to obtain, or otherwise unavailable.

Suggested Citation

  • Brendan Murphy & David Levinson & Andrew Owen, 2015. "Accessibility and Centrality Based Estimation of Urban Pedestrian Activity," Working Papers 000143, University of Minnesota: Nexus Research Group.
  • Handle: RePEc:nex:wpaper:pedestrianactivity
    DOI: 10.25910/Z07C-KX08
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    File URL: http://hdl.handle.net/11299/179834
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    References listed on IDEAS

    as
    1. Zhang, Yuanyuan & Bigham, John & Ragland, David & Chen, Xiaohong, 2015. "Investigating the associations between road network structure and non-motorist accidents," Journal of Transport Geography, Elsevier, vol. 42(C), pages 34-47.
    2. Lowry, Michael, 2014. "Spatial interpolation of traffic counts based on origin–destination centrality," Journal of Transport Geography, Elsevier, vol. 36(C), pages 98-105.
    3. Iacono, Michael & Krizek, Kevin J. & El-Geneidy, Ahmed, 2010. "Measuring non-motorized accessibility: issues, alternatives, and execution," Journal of Transport Geography, Elsevier, vol. 18(1), pages 133-140.
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    Cited by:

    1. Brendan Murphy & David Levinson & Andrew Owen, 2015. "Evaluating the "Safety In Numbers" Effect With Estimated Pedestrian Activity," Working Papers 000136, University of Minnesota: Nexus Research Group.

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    More about this item

    Keywords

    safety; walking; safety-in-numbers; crashes; traffic counts; network structure; accessibility;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • 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
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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