Using a GPS Data Set to Examine the Effects of the Built Environment along Commuting Routes on Travel Outcomes
Publication: Journal of Urban Planning and Development
Volume 140, Issue 4
Abstract
Although extensive research has investigated how the built environment near people’s homes and work places influence automobile travel behavior, little is known about how commuting routes affect travel outcomes. This article presents a methodology that addresses this question by examining the correlation between built environment along commuting routes and vehicle miles traveled (VMT) and fuel consumption for nonwork automobile travel. Using a global positioning systems (GPS) data set collected from automobile trips of 46 drivers from the southeast Michigan area over a 30-day time frame, this study identifies the actual commuting routes for all drivers and derives their fuel consumption for nonwork travel. Although statistically significant relationships are not found between route environments and nonwork VMT and fuel consumption, this study is unique in its focus on the commuting routes and in establishing a methodology for using GPS data in transportation and land-use research, and it offers suggestions for refining the modeling of travel behavior along commuting routes.
Get full access to this article
View all available purchase options and get full access to this article.
References
Adler, T., and Ben-Akiva, M. (1979). “A theoretical and empirical model of trip chaining behavior.” Transport. Res. B Method., 13(3), 243–257.
Ahn, K., Rakha, H., Trani, A., and Van Aerde, M. (2002). “Estimating vehicle fuel consumption and emissions based on instantaneous speed and acceleration levels.” J. Transp. Eng., 182–190.
Ahn, K. R. H., et al. (2002). “Estimating vehicle fuel consumption and emission based on instantaneous speed and acceleration levels.” J. Transp. Eng., 82–190.
Alderson, S., and Stephanedes, Y. (1986). “Transportation corridor strategies and land use.” J. Transp. Eng., 15–28.
Antipova, A., and Wang, F. (2010). “Land use impacts on trip-chaining propensity for workers and nonworkers in Baton Rouge, Louisiana.” Annals GIS, 16(3), 141–154.
Barth, M., et al. (2001). Comprehensive modal emissions model (CMEM), version 2.02, User’s Guide, Center for Environmental Research and Technology, Univ. of California, Riverside, CA.
Bhat, C. R., and Guo, J. Y. (2007). “A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels.” Transport. Res. B Method., 41(5), 506–526.
Boarnet, M. G., and Crane, R. (2001). Travel by design: The influence of urban form on travel, Oxford Univ. Press, New York.
Boarnet, M. G., and Sarmiento, S. (1998). “Can land use policy really affect travel behavior? A study of the link between non-work travel and land use characteristics.” Urban Stud., 35(7), 1155–1169.
Bricka, S., Zmud, J., Wolf, J., and Freedman, J. (2009). “Household travel surveys with GPS.” J. Transport. Res. Board, 2105(1), 51–56.
Brundell-Freij, K., and Ericsson, E. (2005). “Influence of street characteristics, driver category and car performance on urban driving patterns.” Transport. Res. D, 10(3), 213–229.
Cervero, R., and Gorham, R. (1995). “Commuting in transit versus automobile neighborhoods.” J. Am. Plann. Assoc., 61(2), 210–225.
Cervero, R., and Kockelman, K. M. (1997). “Travel demand and the 3Ds: Density, diversity, and design.” Transport. Res. D, 2(3), 199–219.
Chu, Y.-L. (2003). “Empirical analysis of commute stop-making behavior.” J. Transport. Res. Board, 1831(1), 106–113.
Clifton, K. J., and Muhs, C. (2012). “Capturing and representing multimodal trips in travel surveys: Review of the practice.” Transportation Research Board 91st Annual Meeting, Compendium of Papers, Washington, DC.
Crane, R. (1996). “On form versus function: Will the new urbanism reduce traffic, or increase it?” J. Plann. Educ. Res., 15(2), 117–126.
Crane, R. (1999). The impact of urban form on travel: A critical review, Lincoln Institute of Land Policy, Cambridge, MA.
Crane, R. (2000). “The influence of urban form on travel: An interpretive review.” J. Plann. Lit., 15(1), 3–23.
Curtis, F. A., Neilsen, L., and Bjornsor, A. (1984). “Impact of residential street design on fuel consumption.” J. Urban Plann. Dev., 1–8.
Dowling, R., et al. (2005). “Predicting air quality effects of traffic-flow improvements: Final report and user’s guide.” National Cooperative Highway Research Program (NCHRP) Rep. 535, Transportation Research Board.
EPA. (2003). User’s guide to MOBILE 6.1 and MOBILE 6.2: Mobile source emission factor model, U.S. Environmental Protection Agency.
EPA MOBILE 6.2. [Computer software]. U.S. Environmental Protection Agency.
Ericsson, E. (2001). “Independent driving pattern factors and their influence on fuel use and exhaust emission factors.” Transport. Res. D, 6(5), 325–345.
Ewing, R., et al. (2008). Growing cooler: Evidence on urban development and climate change, ULI, Washington, DC.
Ewing, R., et al. (2011). “Traffic generated by mixed-use developments—six-region study using consistent built environmental measures.” J. Urban Plann. Dev., 248–261.
Ewing, R., and Cervero, R. (2001). “Travel and the built environment: A synthesis.” Transport. Res. Rec., 1780(1), 87–114.
Ewing, R., and Cervero, R. (2010). “Travel and the built environment.” J. Am. Plann. Assoc., 76(3), 265–294.
Frank, L. D., et al. (2006). “Many pathways from land use to health.” J. Am. Plann. Assoc., 72(1), 75.
Frank, L. D., Stone, B. J., and Bachman, W. (2000). “Linking land use with household vehicle emissions in the central Puget Sound: Methodological framework and findings.” Transport. Res. D, 5(3), 173–196.
Galster, G., et al. (2001). “Wrestling sprawl to the ground: Defining and measuring an elusive concept.” Housing Pol. Debate, 12(4), 681–717.
Golledge, R. G., and Stimson, R. J. (1987). Analytical behavioural geography, Croom Helm, London.
Grengs, J., Wang, X., and Kostyniuk, L. (2008). “Using GPS data to understand driving behavior.” J. Urban Technol., 15(2), 33–53.
Handy, S. (1993). “Regional versus local accessibility: Implications for nonwork travel.” Transport. Res. Rec., 1400, 58–66.
Handy, S. (2005). “Smart growth and the transportation-land use connection: What does the research tell us?” Int. Regional Sci. Rev., 28(2), 146–167.
Handy, S. L. (1992). “Regional versus local accessibility: Neotraditional development and its implications for non-work travel.” Built Environ., 18(4), 253–267.
Handy, S. L. (1996). “Methodologies for exploring the link between urban form and travel behavior.” Transport. Res. D Transport Environ., 1(2), 151–165.
Hanson, S. (1980). “The importance of the multi-purpose journey to work in urban travel behavior.” Transportation, 9(3), 229–248.
Hanson, S., and Schwab, M. (1987). “Accessibility and intraurban travel.” Environ. Plann. A, 19(6), 735–748.
Kitamura, R., Nishii, K., and Goulias, K. (1990). “Trip chaining behaviour by central city commuters: A causal analysis of time-space constraints.” Develop. Dynam. Activity-Based Approaches to Travel Analysis, P. Jones, ed., Avebury, Aldershot, U.K., 145–170.
Kockelman, K. (1997). “Travel behavior as function of accessibility, land use mixing, and land use balance: Evidence from San Francisco Bay area.” Transport. Res. Rec., 1607(1), 116–125.
Krizek, K. J. (2003a). “Neighborhood services, trip purpose, and tour-based travel.” Transp., 30(4), 387–410.
Krizek, K. J. (2003b). “Operationalizing neighborhood accessibility for land use–travel behavior research and regional modeling.” J. Plann. Educ. Res., 22(3), 270–287.
Kwan, M.-P. (1999). “Gender, the home-work link, and space-time patterns of nonemployment activities.” Econ. Geogr., 75(4), 370–394.
LeBlanc, D., et al. (2006). “Departure crash warning system field operational test: Methodology and results.” UMTRI Report 2006-9-1, Univ. of Michigan Transportation Research Institute, Ann Arbor, MI.
Liu, C., and Shen, Q. (2011). “An empirical analysis of the influence of urban form on household travel and energy consumption.” Comput. Environ. Urban Syst., 35(5), 347–357.
Lynch, D. (1960). The image of the city, MIT Press, Cambridge, MA.
Maat, K., and Timmermans, H. J. P. (2009). “Influence of the residential and work environment on car use in dual-earner households.” Transport. Res. Part A Pol. Prac., 43(7), 654–664.
MCGI. (2006). “Framework classification code: Field definitions and valid entries.” 〈http://www.mcgi.state.mi.us/mgdl/〉 (Jan. 3, 2008).
Menghini, G., Carrasco, N., Schüssler, N., and Axhausen, K. W. (2010). “Route choice of cyclists in Zurich.” Transp. Res. Part A Policy Pract., 44(9), 754–765.
MI geographic data library. (2008). “Center for geographic information (CGI), State of Michigan.” 〈http://www.mcgi.state.mi.us/mgdl/?rel=ext&action=sext〉 (Mar. 2008).
NHTS. (2001). “2001 national household travel survey.” Federal Highway Administration, 〈http://www.nhts.ornl.gov/〉.
Oswald, M., and McNeil, S. (2010). “Rating sustainability: Transportation investments in urban corridors as a case study.” J. Urban Plann. Dev., 177–185.
Pollack, A. K., et al. (2004). Evaluation of the U.S. EPA MOBILE6 highway vehicle emission factor model, ENVIRON International Corporation.
Rakha, H., Ahn, K., and Trani, A. (2004). “Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions.” Transport. Res. Part D Transport Environ., 9(1), 49–74.
Rosenbloom, S. (2003). The mobility needs of older Americans: Implications for transportation reauthorization, Brookings Institution, Washington, DC.
Saxena, S., and Mokhtarian, P. L. (1997). “The impact of telecommuting on the activity spaces of participants.” Geogr.Anal., 29(2), 124–144.
Song, G., Yu, L., and Wang, Z. (2009). “Aggregate fuel consumption model of light-duty vehicles for evaluating effectiveness of traffic management strategies on fuels.” J. Transp. Eng., 611–618.
Song, Y., and Knaap, G.-J. (2004). “Measuring urban form: Is Portland winning the war on sprawl?” J. Am. Plann. Assoc., 70(2), 201–225.
Southworth, F. (1985). “Multi-destination, multi-purpose trip chaining and its implications for locational accessibility: A simulation approach.” Papers Regional Sci., 57(1), 107–123.
Steiner, R. L. (1994). “Residential density and travel patterns: Review of the literature.” Transport. Res. Board, 1466, 37–43.
TRB. (2005). “Does the built environment influence physical activity? Examing the evidence.” Transportation Research Board, Institute of Medicine of the National Academies, Washington, DC.
VT-Micro. [Computer software]. Virginia Tech Transportation Institute.
Wachs, M. (1979). Transportation for the elderly: Changing lifestyles, changing needs, Univ. of California Press, Berkeley, CA.
Wachs, M. (1987). “Men, women, and wheels: The historical basis of sex differences in travel patterns.” Transport. Res. Rec., 1135, 10–16.
Witten, K., Pearce, J., and Day, P. (2011). “Neighbourhood destination accessibility index: A GIS tool for measuring infrastructure support for neighbourhood physical activity.” Environ. Plann. A, 43(1), 205–223.
Information & Authors
Information
Published In
Journal of Urban Planning and Development
Volume 140 • Issue 4 • December 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Dec 5, 2012
Accepted: Aug 30, 2013
Published online: Sep 2, 2013
Discussion open until: Jul 12, 2014
Published in print: Dec 1, 2014
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.