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Evaluating light rail sketch planning: actual versus predicted station boardings in Phoenix

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In recent years, transit planners are increasingly turning to simpler, faster, and more spatially detailed “sketch planning” or “direct demand” models for forecasting rail transit boardings. Planners use these models for preliminary review of corridors and analysis of station-area effects, instead of or prior to four-step regional travel demand models. This paper uses a sketch-planning model based on a multiple regression originally fitted to light-rail ridership data for 268 stations in nine U.S. cities, and applies it predictively to the Phoenix, Arizona light-rail starter line that opened in December, 2008. The independent variables in the regression model include station-specific trip generation and intermodal–access variables as well as system-wide variables measuring network structure, climate, and metropolitan-area factors. Here we compare the predictions we made before and after construction began to pre-construction Valley Metro Rail predictions and to the actual boardings data for the system’s first 6 months of operations. Depending on the assumed number of bus lines at each station, the predicted total weekday ridership ranged from 24,767 to 37,907 compared with the average of 33,698 for the first 6 months, while the correlation of predicted and observed station boardings ranged from r = 0.33 to 0.47. Sports venues, universities, end-of-line stations, and the number of bus lines serving each station appear to account for the major over- and under-predictions at the station level.

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  • Atkinson-Palombo, C., Kuby, M.: The geography of advance transit-oriented development in metropolitan Phoenix, Arizona, 2000–2007. J. Transp. Geogr. 19, 189–199 (2011)

    Article  Google Scholar 

  • Boyle, D.: Easy to apply, short range, fixed-route, bus and rail transit ridership forecasting methods. Transit Cooperative Research Program (TCRP) Synthesis Report 66 (2006)

  • Cervero, R.: Alternative approaches to modeling the travel-demand impacts of smart growth. J. Am. Plann. Assoc. 72, 285–295 (2006)

    Article  Google Scholar 

  • Chu, X.: Ridership models at the stop level. National Center of Transit Research, University of South Florida, Tampa (2004)

    Google Scholar 

  • Dickey, J.W.: Metropolitan Transportation Planning, 2nd edn. McGraw Hill, New York (1983)

    Google Scholar 

  • Energy Information Administration.: Annual U.S. all grades reformulated retail gasoline prices. (2010). Accessed 5 August 2010

  • Estupiñán, N., Rodríguez, D.A.: The relationship between urban form and station boardings for Bogota’s BRT. Transp. Res. A 42, 296–306 (2008)

    Google Scholar 

  • Ewing, R.: Pedestrian- and transit-friendly design. Florida Department of Transportation, Appendix C, Tallahassee (1996)

    Google Scholar 

  • Ewing, R., Cervero, R.: Travel and the built environment: a synthesis. Transp. Res. Rec. 1780, 87–113 (2001)

    Article  Google Scholar 

  • Federal Transit Administration: Discussion-Piece #8, CTPP-based Aggregate Model (2006). Accessed 23 April 2013

  • Federal Transit Administration, Office of Planning and Environment.: Reporting: instructions for the section 5309 new starts criteria. U.S. Department of Transportation, Washington, DC (2011)

  • Federal Transit Administration.: Before and after studies of new starts projects. U.S. Department of Transportation, Washington, DC (2013). Accessed 23 April 23 2013

  • Florida Department of Transportation (FDOT).: Public Transit Office: T-BEST (Transit Boardings Estimation and Simulation Tool), Tallahassee, FL (2010). Accessed 5 Aug 2010

  • Flyvbjerg, B., Holm, M.S., Buhl, S.: Underestimating costs in public works projects: error or lie? J. Am. Plann. Assoc. 68, 279–295 (2002)

    Article  Google Scholar 

  • Goulias, K.G.: Activity-based travel forecasting: what are some issues? In: Texas Transportation Institute (ed.) Activity-Based Travel Forecasting Conference, 2–5 June 1996: Summary, Recommendations, and Compendium of Papers, Travel Model Improvement Program, pp. 37–49. US Department of Transportation, US Environmental Protection Agency, Washington, DC (1997)

  • Guhathakurta, S.: Urban modelling as storytelling: using simulation models as a narrative. Environ. Plann. B 29, 895–911 (2002)

    Article  Google Scholar 

  • Horowitz, A.J.: Transit Ridership Forecasting Model: Reference Manual. Urban Mass Transportation Administration, US Department of Transportation, Washington, DC (1985)

    Google Scholar 

  • Johnston, R.A.: The urban transportation planning process. In: Hanson, S. (ed.) The Geography of Urban Transportation, 3rd edn, pp. 115–140. Guilford Press, New York (2004)

    Google Scholar 

  • Kaplan, B., Englisher, L., Warner, M.: Actual versus forecast ridership on the MetroLink in St. Clair County, Illinois. In: Circular E-C058: 9th National Light Rail Transit Conference (2003)

  • Kitamura, R., Chen, C., Pendyala, R. M., Narayaran, R.: Micro-simulation of daily activity-travel patterns for travel demand forecasting. Transportation 27, 25–51 (2000)

    Google Scholar 

  • Kuby, M., Barranda, A., Upchurch, C.: Factors influencing light rail station boardings in the United States. Transp. Res. A 38, 223–247 (2004)

    Google Scholar 

  • Lane, C., DiCarlantonio, M., Usvyat, L.: Sketch models to forecast commuter and light rail ridership: update to TCRP report 16. Transp. Res. Rec. 1986, 198–210 (2006)

    Article  Google Scholar 

  • Levinson, H.S.: Forecasting future transit route ridership. Transp. Res. Rec. 1036, 19–28 (1985)

    Google Scholar 

  • Malczewski, J.: Spatial decision support systems. NCGIA Core Curriculum in Geographic Information Science (1997). Accessed 5 Aug 2010

  • Mayworm, P.D., Lago, A.M., McEnroe, J.M.: Patronage impacts of changes in transit fares and services. Urban Mass Transportation Agency, Washington, DC (1980)

    Google Scholar 

  • Menhard, H.R., Ruprecht, G.F.: Review of route-level ridership prediction techniques. Transp. Res. Rec. 936, 22–24 (1983)

    Google Scholar 

  • Parsons Brinckerhoff Quade & Douglas Inc.: Transit and urban form. National Academy Press, Washington, DC (1996)

    Google Scholar 

  • Peng, Z.-R., Dueker, Kj., Strathman, J., Hopper, J.: A simultaneous route-level transit patronage model: demand, supply, and inter-route relationship. Transportation 24, 159–181 (1997)

    Article  Google Scholar 

  • Pickrell, D.H.: A desire named streetcar: fantasy and fact in rail transit planning. J. Am. Plann. Assoc. 58(2), 158–176 (1992)

    Article  Google Scholar 

  • Pratt, R.H., Pederson, N.J., Mather, J.J.: Traveler Response to Transportation System Changes: A Handbook for Transportation Planners. Federal Highway Administration, Washington, DC (1977)

    Google Scholar 

  • Pratt, R.H., Coople, J.N.: Traveler Response to Transportation System Changes, 2nd edn. Federal Highway Administration, Washington, DC (1981)

    Google Scholar 

  • Pushkarev, B.J., Zupan, M., Cumella, R.S.: Urban Rail in America: An Exploration of Criteria for Fixed Guideway Transit. Indiana University Press, Bloomington (1982)

    Google Scholar 

  • Saur, G. J., Lee, R., Gray, C.: New method for transit ridership forecasting. In: Institute of Transportation Engineers District 6, 2004 Annual Meeting and Exhibit Compendium CD, Lake Buena Vista, FL (2004)

  • Smith, L., Beckman, R., Anson, D., Nagel, K., Williams, M.E.: TRANSIMS: transportation analysis and simulation system. In: Proceedings of the 5th National Conference on Transportation Planning Methods Application, vol. 2. Transportation Research Board, Washington, DC (1995)

  • Sohn, K., Shim, H.: Factors generating boardings at metro stations in the Seoul metropolitan area. Cities 27, 358–368 (2010)

    Article  Google Scholar 

  • Stopher, P.S.: Development of a route-level patronage forecasting method. Transportation 19, 201–220 (1992)

    Article  Google Scholar 

  • Taylor, B.D., Fink, C.N.Y.: The factors influencing transit ridership: a review and analysis of ridership literature. Working Paper. UCLA Department of Urban Planning, Los Angeles (2003)

  • Ulberg, C.: Short-term ridership projection model. Transp. Res. Rec. 854, 12–16 (1982)

    Google Scholar 

  • Upchurch, C., Kuby, M., Zoldak, M., Barranda, A.: Using GIS to generate mutually exclusive service areas linking travel on and off a network. J. Transp. Geogr. 12, 23–33 (2004)

    Article  Google Scholar 

  • Wachs, M.: Technique vs. advocacy in forecasting: a study of rail rapid transit. Urban Res. 4(1), 23–30 (1986)

    Google Scholar 

  • Waddell, P.: Modeling urban development for land use, transportation, and environmental planning. J. Am. Plann. Assoc. 68, 297–314 (2002)

    Article  Google Scholar 

  • Woodford, B.: The ARRF II model. In: FTA Workshop on Travel Forecasting for New Starts (2009). Accessed 23 April 2013

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The authors thank three anonymous reviewers and Editor David T. Hartgen for comments on earlier versions of the paper, as well as Michael Palmer and Scott Kelley of ASU for their assistance with GIS, and James Ryan of FTA for helpful information about FTA policy and practice.

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Correspondence to Michael Kuby.

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Upchurch, C., Kuby, M. Evaluating light rail sketch planning: actual versus predicted station boardings in Phoenix. Transportation 41, 173–192 (2014).

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