Transportation impacts of affordable housing: Informing development review with travel behavior analysis


  • Amanda Howell Portland State University
  • Kristina Currans University of Arizona
  • Steven Gehrke Portland State University
  • Gregory Norton Portland State University
  • Kelly Clifton Portland State University



Affordable housing, transportation impact analysis, vehicle miles traveled, vehicle ownership, low-income, land use


Planning for affordable housing is challenged by development policies that assess transportation impacts based on methodologies that often do not distinguish between the travel patterns of residents of market-rate housing and those living in affordable units. Given the public goals of providing affordable housing in areas with good accessibility and transportation options, there is a need to reduce unnecessary costs imposed by the potential overestimation of automobile travel and its associated impacts. Thus, the primary objective of this paper is to examine and quantify the influences of urban characteristics, residential housing type, and income on metrics commonly used to assess the transportation impacts of new development, namely total home-based trips and home-based vehicle trips. Using the 2010-2012 California Household Travel Survey, we regressed these metrics on urban place type, regionally adjusted income, and housing type, controlling for household size, weekday travel, and home location. The results indicate significant reductions in vehicle trip making with lower incomes and increasing urbanization. These findings support more differentiation of affordable and market-rate housing in the development review process and emphasize the need for development standards to be more sensitive to the characteristics of future residents and location.


Bates, L. (2016). State income limits for 2016. Sacramento, CA: Department of Housing and Community Development, Division of Housing Policy Development. Retrieved from

Blumenberg, E., & Pierce, G. (2012). Automobile ownership and travel by the poor: Evidence from the 2009 National Household Travel Survey. Transportation Research Record, 2320(1), 28–36. doi:10.3141/2320-04

Caltrans. (2010). Smart mobility 2010: A call to action for the new decade. Sacramento, CA: Caltrans.

Chatman, D. G. (2013). Does TOD need the T? Journal of the American Planning Association, 79(1), 17–31. doi:10.1080/01944363.2013.791008

City of Pasadena Permit Center. (2015). Miscellaneous fees and charges. Retrieved from

City of Sacramento Community Development Department. (2017). Sacramento Transportation Authority STA fee table. Retrieved from

Clifton, K. J., Currans, K. M., & Muhs, C. D. (2013). Evolving the Institute of Transportation Engineers trip generation handbook: A proposal for collecting multi-modal, multi-context, establishment-level data. Transportation Research Record, 2344(2), 107–117.

Currans, K. M. (2017). Issues in urban trip generation. Portland, Oregon: Portland State University.

Dock, S., Cohen, L., Rogers, J. D., Henson, J., Weinberger, R., Schrieber, J., & Ricks, K. (2015). Methodology to gather multimodal urban trip generation data. Paper presented at the Annual Meeting of the Transportation Research Board, Washington, DC.

Ewing, R., & Cevero, R. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76(3), 265–294.

Giuliano, G. (2005). Low income, public transit, and mobility. Transportation Research Record, 1927(1), 63–70.

Giuliano, G., & Dargay, J. (2006). Car ownership, travel and land use: A comparison of the U.S. and Great Britain. Transportation Research Part A, 40(1), 106–124.

Handy, S. (1993). Regional versus local accessibility: Implications for nonwork travel. Transportation Research Record, 1400, 58–66.

Holtzclaw, J., Clear, R., Dittmar, H., Goldstein, D., & Haas, P. (2002). Location efficiency: Neighborhood and socioeconomic characteristics determine auto ownership and use—Studies in Chicago, Los Angeles and San Francisco. Transportation Planning and Technology, 25(1), 1–27. doi:10.1080/03081060290032033

Institute of Transportation Engineers. (2012). Trip generation manual (9th ed.). Washington, DC: Institute of Transportation Engineers.

Institute of Transportation Engineers. (2014). Trip generation handbook, 3rd Edition: An ITE recommended practice. Washington, DC: Institute of Transportation Engineers.

Joint Center for Housing Studies. (2015). America’s rental housing: Expanding options for diverse and growing demand. Cambridge, MA: Harvard University.

Kimley-Horn and Associates, Inc., Economic & Planning Systems, & Gene Bregman & Associates. (2009). Trip-generation rates for urban infill land uses in California: Phase 2, data collection. Sacramento, CA: California Department of Transportation. Retrieved from

Manville, M. (2013). Parking requirements and housing development. Journal of the American Planning Association, 79(1), 49–66. doi:10.1080/01944363.2013.785346

Millard-Ball, A. (2015). Phantom trips: Overestimating the traffic impacts of new development. Journal of Transport and Land Use, 8(1), 1–19.

Murakami, E., & Young, J. (1997). Daily travel by persons with low income. Paper presented at the National Person Travel Survey Symposium, Bethesda, MD.

Newmark, G. L., & Haas, P. M. (2015, December 16). Income, location efficiency, and VMT: Affordable housing as a climate strategy. Retrieved from

Ong, P. M., & Houston, D. (2002). Transit, employment and women on welfare. Urban Geography, 23(4), 344–364.

Pucher, J., & Renne, J. L. (2003). Socioeconomics of urban travel: Evidence from the 2001 NHTS. Transportation Quarterly, 57(3), 49–77.

Rindt, C. (2015). How to create the linked trip table. Irvine, California: University of California, Irvine, for Caltrans.

Rogers, J., Emerine, D., Haas, P., Jackson, D., Kauffmann, P., Rybeck, R., & Westrom, R. (2016). Estimating parking utilization in multi-family residential buildings in Washington, DC. Paper presented at the Annual Meeting of the Transportation Research Board, Washington, DC.

Rowe, D., Morse, S., Ratchford, C., Haas, P., & Becker, S. (2014). Modeling of multifamily residential parking use in King County, Washington. Transportation Research Record, 2469(1), 57–64. doi:10.3141/2469-07

Salon, D. (2015). Heterogeneity in the relationship between the built environment and driving: Focus on neighborhood type and travel purpose. Research in Transportation Economics, 52(1), 34–45.

Schneider, R. J., Shafizadeh, K., & Handy, S. L. (2015). Method to adjust Institute of Transportation Engineers vehicle trip-generation estimates in smart-growth areas. Journal of Transport and Land Use, 8(1), 69–83.

Schneider, R. J., Shafizadeh, K., Sperry, B. R., & Handy, S. L. (2013). Methodology to gather multimodal trip generation data in smart-growth areas. Transportation Research Record, 2354, 68–85.

Steffen, B. L., Carter, G. R., Martin, M., Pelletiere, D., Vandenbroucke, D. A., & Yao, Y.-G.D. (2015). Worst case housing needs: 2015 report to Congress. Washington, DC: US Department of Housing and Urban Development.

Tal, G., & Handy, S. (2010). Travel behavior of immigrants: An analysis of the 2001 National Household Transportation Survey. Transport Policy, 17(1), 85–93.

The Center for Neighborhood Technology. (2012). Safe, decent, and affordable: Transportation costs of affordable housing in the Chicago region. Chicago, IL: The Center for Neighborhood Technology.

U.S. Environmental Protection Agency. (2014, April 10). Smart location database. Retrieved from

Weinberger, R., Dock, S., Cohen, L., Rogers, J., & Henson, J. (2015). Predicting travel impacts of new development in America’s major cities: Testing alternative trip generation models. Paper presented at the 92nd Annual Meeting of the Transportation Research Board, Washington, DC.




How to Cite

Howell, A., Currans, K., Gehrke, S., Norton, G., & Clifton, K. (2018). Transportation impacts of affordable housing: Informing development review with travel behavior analysis. Journal of Transport and Land Use, 11(1).