The Impact of Urban Spatial Structure on Travel Demand in the United States
By Antonio M. Bento, M. Cropper, A. M. Mobarak, K. Vinha. 2003
443 citations recorded by the source corpus.
The authors combine measures of urban form and public transit supply for 114 urbanized areas with the 1990 Nationwide Personal Transportation Survey to address two questions: (1) How do measures of urban form, including city shape, road density, the spatial distribution of population, and jobs-housing balance affect the annual miles driven and commute mode choices of U.S. households? (2) How does the supply of public transportation (annual route miles supplied and availability of transit stops) affect miles driven and commute mode choice? The authors find that jobs-housing balance, population centrality, and rail miles supplied significantly reduce the probability of driving to work in cities with some rail transit. Population centrality and jobs-housing balance have a significant impact on annual household vehicle miles traveled (VMT), as do city shape, road density, and (in rail cities) annual rail route miles supplied. The elasticity of VMT with respect to each variable is small, on the order of 0.10-0.20 in absolute value. However, changing several measures of form simultaneously can reduce annual VMT significantly. Moving the sample households from a city with the characteristics of Atlanta to a city with the characteristics of Boston reduces annual VMT by 25 percent.
Subfields: Building and Construction, Transportation
View Paper: https://www.semanticscholar.org/paper/21a25745f895f9a3b5721b88e5450cbd2d9ee037
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Citations in the corpus
- Urban Polycentricity and the Costs of Commuting: Evidence from Italian Metropolitan Areas (2010, unknown): “1998), while others show the contrary ( Bento et al., 2005 ).”
- Modeling Private Car Ownership in China (2010, background): “(18), and Prevedouros and Schofer (19), Kim and Kim in 2004 provided evidence that transit access and transit service had a significant negative effect on the number of automobiles owned (20).”
- A Meta-Analysis of Global Urban Land Expansion (2011, background): “The spatial form of cities, especially urban transportation infrastructure and residential density, affects travel demand [9], energy consumption [10], and automobile use [11].”
- A discrete–continuous model of households’ vehicle choice and usage, with an application to the effects of residential density (2008, background): “In Bento et al. (2003), a 10% increase in population centrality is found to reduce annual miles travelled by approximately 300 miles. me to gauge whether the association between the errors are important enough to be taken into consideration.”
- An Empirical Analysis of Urban Form, Transport, and Global Warming (2008, background): “In disaggregate studies (e.g., Boarnet and Sarmiento, 1998, Crane and Crepeau, 1998, Giuliano and Narayan, 2003; Handy et al., 2005; Bento et al. 2005) the dependent variable (e.”
- Modeling energy consumption and CO2 emissions at the urban scale: Methodological challenges and insights from the United States (2010, background): “Bento et al. (2005), who found that household characteristics have a stronger influence on commute-mode choice than urban-scale characteristics, do not directly analyze energy consumption, but their study is a good example of a careful statistical analysis.”
- Quantitative analysis of urban form: a multidisciplinary review (2008, background): “( 2002 ) find that the jobs–housing balance, population centrality, and rail miles supplied lower the probability of travel to work by car and vehicle‐miles traveled, though the elasticities are small.”
- Urban Structure and Energy—A Review (2008, methodology): “, 2006); rail supply and ridership (Bento et al., 2003); income and car ownership (Bento et al., 2003); income and fuel use (Golob & Brownstone, 2005); public transport travel times and patronage (Camagni et al., 2002). The expected negative link is found between VKT and fuel price (Johansson & Schi”