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Community design and how much we drive

Author

Listed:
  • Wesley Marshall

    (University of Colorado Denver)

  • Norman Garrick

    (University of Connecticut)

Abstract

The preponderance of evidence suggests that denser and more connected communities with a higher degree of mixed land uses results in fewer vehicle kilometers traveled (VKT). However, there is less agreement as the size of the effect. Also, there is no clear understanding as to the aspects of community design that are most important in contributing to lower VKT. One reason why there is some confusion on this point is that past studies have not always made a clear distinction between different community and street network design characteristics such as density, connectivity, and configuration. In this research, care was taken to fully characterize the different features of the street network including a street pattern classification system that works at the neighborhood level but also focuses on the citywide street network as a separate entity. We employ a spatial kriging analysis of NHTS data in combination with a generalized linear regression model in order to examine the extent to which community design and land use influence VKT in 24 California cities of populations from 30,000 to just over 100,000. Our results suggest that people living in denser street network designs tended to drive less. Connectivity, however, played an adverse role in performance.

Suggested Citation

  • Wesley Marshall & Norman Garrick, 2012. "Community design and how much we drive," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(2), pages 5-21.
  • Handle: RePEc:ris:jtralu:0079
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    References listed on IDEAS

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    1. Mindali, Orit & Raveh, Adi & Salomon, Ilan, 2004. "Urban density and energy consumption: a new look at old statistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(2), pages 143-162, February.
    2. Daniel J. Graham & Stephen Glaister, 2003. "Spatial Variation in Road Pedestrian Casualties: The Role of Urban Scale, Density and Land-use Mix," Urban Studies, Urban Studies Journal Limited, vol. 40(8), pages 1591-1607, July.
    3. Crane, Randall, 1998. "Travel By Design?," University of California Transportation Center, Working Papers qt3pc4v6jj, University of California Transportation Center.
    4. Crane, Randall & Crepeau, Richard, 1998. "Does Neighborhood Design Influence Travel?: Behavioral Analysis of Travel Diary and GIS Data," University of California Transportation Center, Working Papers qt4pj4s7t8, University of California Transportation Center.
    5. Su, Qing, 2010. "Travel demand in the US urban areas: A system dynamic panel data approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(2), pages 110-117, February.
    6. Heres-Del-Valle, David & Niemeier, Deb, 2011. "CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 150-161, January.
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    Cited by:

    1. Parthasarathi, Pavithra & Levinson, David, 2018. "Network structure and the journey to work: An intra-metropolitan analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 292-304.
    2. Martin Scoppa & Rim Anabtawi, 2021. "Connectivity in Superblock Street Networks: Measuring Distance, Directness, and the Diversity of Pedestrian Paths," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    3. Scoppa, Martin & Bawazir, Khawla & Alawadi, Khaled, 2019. "Straddling boundaries in superblock cities. Assessing local and global network connectivity using cases from Abu Dhabi, UAE," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 770-782.
    4. Wang, Shiguang & Yu, Dexin & Kwan, Mei-Po & Zheng, Lili & Miao, Hongzhi & Li, Yongxing, 2020. "The impacts of road network density on motor vehicle travel: An empirical study of Chinese cities based on network theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 144-156.
    5. Andrew Perumal & David Timmons, 2017. "Contextual Density and US Automotive CO2 Emissions across the Rural–Urban Continuum," International Regional Science Review, , vol. 40(6), pages 590-615, November.
    6. Choi, Dong-ah & Ewing, Reid, 2021. "Effect of street network design on traffic congestion and traffic safety," Journal of Transport Geography, Elsevier, vol. 96(C).

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    More about this item

    Keywords

    community design; land use mix; street network; National Household Travel Survey; spatial kriging an;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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