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Vehicle Miles Traveled and the Built Environment: Evidence from Vehicle Safety Inspection Data

Author

Listed:
  • M i Diao

    (Department of Real Estate, National University of Singapore, 4 Architecture Drive, Singapore 117566)

  • Joseph Ferreira Jr

    (Department of Urban Studies and Planning, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA)

Abstract

This study examines the linkage between household vehicle usage and their residential locations within a metropolitan area using a newly available administrative dataset of annual private passenger vehicle safety inspection records (with odometer readings) and spatially detailed data on the built environment. Vehicle miles travelled (VMT) and a set of comprehensive built-environment measures are computed for a statewide 250 × 250 m grid cell layer using advanced geographic information systems and database management tools. We apply factor analysis to construct five factors that differentiate the built-environment characteristics of the grid cells and then integrate the built-environment factors into spatial regression models of household vehicle usage that account for built environment, demographics, and spatial interactions. The empirical results suggest that built-environment factors not only play an important role in explaining the intraurban variation of household vehicle usage, but may also be underestimated by previous studies that use more aggregate built-environment measures. One-standard-deviation variations in the built-environment factors are associated with as much as 5000-mile differences in annual VMT per household. This study also demonstrates the potential value of new georeferenced administrative datasets in developing indicators that can assist urban planning and urban management.

Suggested Citation

  • M i Diao & Joseph Ferreira Jr, 2014. "Vehicle Miles Traveled and the Built Environment: Evidence from Vehicle Safety Inspection Data," Environment and Planning A, , vol. 46(12), pages 2991-3009, December.
    • Handle: RePEc:sae:envira:v:46:y:2014:i:12:p:2991-3009
    DOI: 10.1068/a140039p
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    References listed on IDEAS

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    Cited by:

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    2. Benita, Francisco & Piliouras, Georgios, 2020. "Location, location, usage: How different notions of centrality can predict land usage in Singapore," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. Song, Siqi & Diao, Mi & Feng, Chen-Chieh, 2016. "Individual transport emissions and the built environment: A structural equation modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 206-219.
    4. Hatamzadeh, Yaser, 2021. "Working commuters’ tendency toward a travel pattern with potentially more walking: Examining the relative influence of personal and environmental measures," Research in Transportation Economics, Elsevier, vol. 86(C).
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    6. Chatterton, T. & Anable, J. & Cairns, S. & Wilson, R.E., 2018. "Financial Implications of Car Ownership and Use: a distributional analysis based on observed spatial variance considering income and domestic energy costs," Transport Policy, Elsevier, vol. 65(C), pages 30-39.
    7. Diao, Mi, 2019. "Towards sustainable urban transport in Singapore: Policy instruments and mobility trends," Transport Policy, Elsevier, vol. 81(C), pages 320-330.
    8. Enhui Chen & Zhirui Ye & Hui Bi, 2019. "Incorporating Smart Card Data in Spatio-Temporal Analysis of Metro Travel Distances," Sustainability, MDPI, vol. 11(24), pages 1-22, December.

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