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Original Articles

Ex-Post Evaluations of Demand Forecast Accuracy: A Literature Review

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Pages 540-557 | Received 09 Jun 2013, Accepted 17 May 2014, Published online: 10 Jun 2014

References

  • American Public Transit Association. (1991). Fare elasticity and its application to forecasting transit demand. Washington, DC: Author.
  • Ascher, W. (1981). The forecasting potential of complex models. Policy Sciences, 13(3), 247–267.
  • Bain, R. (2009). Error and optimism bias in toll road traffic forecasts. Transportation, 36(5), 469–482.
  • Banister, D. (2008). The sustainable mobility paradigm. Transport Policy, 15, 73–80.
  • Banister, D., & Thurstain-Goodwin, M. (2011). Quantification of the non-transport benefits resulting from rail investment. Journal of Transport Geography, 19, 212–223.
  • Brinkman, A. (2003). The ethical challenges and professional responses of travel demand forecasters (PhD thesis). University of California, Berkeley.
  • Button, K. J., Doh, S., Hardy, M. H., Yuan, J., & Xin, Z. (2010). The accuracy of transit system ridership forecasts and capital cost estimates. International Journal of Transport Economics, 37(2), 155–168.
  • Clarke, M., Dix, M., & Jones, P. (1981). Error and uncertainty in travel surveys. Transportation, 10(2), 105–126.
  • Cox, W., & Moore, A. (2012). The XpressWest High-speed rail line from Victorville to Las Vegas: A taxpayer risk analysis. Reason Foundation. Retrieved April 10, 2013, from http://reason.org/studies/show/the-xpresswest-high-speed-rail-line
  • De Jong, G., Daly, A., Pieters, M., Miller, S., Plasmeijer, R., & Hofman, F. (2007). Uncertainty in traffic forecasts: Literature review and new results for the Netherlands. Transportation, 34(4), 375–395.
  • De Jongh, P. (1998). Uncertainty in EIA. In P. Warthern (Ed.), Environmental impact assessment: Theory and practice (New ed., pp. 62–83). London: Routledge.
  • Department of Transportation. (2007). Contractor performance assessment report. US Department of Transportation, Federal Transit Administration, Office of Planning and Environment.
  • Department of Transportation. (2008). The predicted and actual impacts of the new starts projects 2007. US Department of Transportation, Federal Transit Administration, Office of Planning and Environment.
  • Eliasson, J., & Fosgerau, M. (2013). Cost overruns and demand shortfalls — deception or selection? Transportation Research Part B: Methodological, 57, 105–113. doi:10.1016/j.trb.2013.09.005
  • Flyvbjerg, B. (2007). Megaproject policy and planning: Problems, causes, cures (Doctoral dissertation). Aalborg University.
  • Flyvbjerg, B., Holm, M. K. S., & Buhl, S. L. (2006). Inaccuracy in traffic forecasts. Transport Reviews, 26(1), 1–24.
  • Goodwin, P. (2012). Peak travel, peak car and the future of mobility. Presented at the international transport forum, Leipzig.
  • Hall, P. (1980). Great planning disasters. London: Weidenfeld & Nicholson.
  • Hartgen, D. T. (2013). Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling. Transportation, 40(6), 1133–1157. doi:10.1007/s11116-013-9497-y
  • Hayashi, Y., & Morisugi, H. (2000). International comparison of background concept and methodology of transportation project appraisal. Transport Policy, 7(1), 73–88.
  • Highways Agency. (2011). Post opening project evaluation of major schemes (2002 to 2009): Meta analysis (Main Report). UK Highways Agency.
  • Kahneman, D. (2011). Thinking, fast and slow (1st ed.). New York: Farrar, Straus and Giroux.
  • Kain, J. F. (1990). Deception in Dallas. Strategic misrepresentation in rail transit promotion and evaluation. Journal of the American Planning Association, 56(2), 184–196.
  • Kharbanda, O. P., & Stallworthy, E. A. (1983). How to learn from project disasters. True-life stories with a moral for management. Aldershot: Gower.
  • Ladd, B. (2012). You can't build your way out of congestion— or can you? disP — The Planning Review, 48(3), 16–23.
  • Li, Z., & Hensher, D. (2010). Toll roads in Australia: An overview of characteristics and accuracy of demand forecasts. Transport Reviews, 30(5), 541–569.
  • Litman, T. (2012). Generated traffic and induced travel. Implications for transport planning. Victoria: Victoria Transport Policy Institute.
  • Mackie, P. (2010). Cost-benefit analysis in transport. A UK perspective. Discussion papers from the international transport forum, Mexico.
  • Mackinder, I. E., & Evans, S. E. (1981). The predictive accuracy of British transport studies in urban areas (No. 699). Crowthorne: Transport and Road Research Laboratory.
  • Marte, G. (2003). Slow vehicle traffic is a more attractive alternative to fast vehicle traffic than public transport. World Transport Policy & Practice, 9(2), 18–23.
  • Mogridge, M. J. H. (1997). The self-defeating nature of urban road capacity policy. Transport Policy, 4(1), 5–23.
  • MOTOS. (2007). Transport modelling: Towards operational standards in Europe (Handbook No. MOTOS/M2.1/PU/v1.0). MOTOS project EU.
  • Næss, P., Nicolaisen, M. S., & Strand, A. (2012). Traffic Forecasts ignoring induced demand: A shaky fundament for cost-benefit analyses. European Journal of Transport and Infrastructure Research, 12(3), 291–309.
  • National Audit Office. (1988). Department of transport, Scottish development department and Welsh office: Road planning (No. 688). London: Author.
  • Nicolaisen, M. S. (2012). Forecasts: Fact or fiction? Uncertainty and inaccuracy in transport project evaluation (PhD thesis). Aalborg University.
  • Nielsen, O. A., & Fosgerau, M. (2005). Overvurderes tidsbenefit af vejprojekter? Proceedings from the annual transport conference at Aalborg University, Aalborg.
  • Odgaard, T., Kelly, C., & Laird, J. (2005). Current practice in project appraisal in Europe. Analysis of country reports (No. Deliverable 1/Volume 1). European Commission EC-DG TREN.
  • Olsson, N. O. E., Krane, H. P., Rolstadås, A., & Veiseth, M. (2010). Influence of reference points in ex post evaluations of rail infrastructure projects. Transport Policy, 17(4), 251–258. doi:10.1016/j.tranpol.2010.01.008
  • Parthasarathi, P., & Levinson, D. (2010). Post construction evaluation of traffic forecast accuracy. Transport Policy, 12(6), 428–443.
  • Pickrell, D. H. (1990). Urban rail transit projects: Forecast versus actual ridership and cost. Washington, D.C.: Urban Mass Transportation Administration.
  • Rasouli, S., & Timmermans, H. (2012). Uncertainty in travel demand forecasting models: Literature review and research agenda. Transportation Letters. The International Journal of Transportation Research, 4(1), 55–73.
  • Sager, T., & Ravlum, I. A. (2005). The political relevance of planners’ analysis. The case of a parliamentary standing committee. Planning Theory, 4(1), 33–65.
  • Salling, K. B., & Bannister, D. (2009). Assessment of large transport infrastructure projects: The CBA-DK model. Transportation Research Part A, 43, 800–813.
  • Salling, K. B., & Leleur, S. (2006). Assessment of transport infrastructure projects by the use of Monte Carlo simulation. The CBA-DK model. Proceedings of the 2006 winter simulation conference, Monterey, 1537–1544.
  • Siemiatycki, M. (2009). Academics and auditors. Comparing perspectives on transportation project cost overruns. Journal of Planning Education and Research, 29(2), 142–156. doi:10.1177/0739456X09348798
  • Skaburskis, A., & Teitz, M. B. (2003). Forecasts & outcomes. Planning Theory and Practise, 4(4), 429–442.
  • Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
  • Van Wee, B. (2007). Large infrastructure projects: A review of the quality of demand forecasts and cost estimations. Environment and Planning B: Planning and Design, 34(4), 611–625.
  • Walker, W. E., Harremöes, P., Rotmans, J., Van Der Sluijs, J. P., Van Asselt, M. B. A., Janssen, J., … Krauss, M. P. (2003). Defining uncertainty a conceptual basis for uncertainty management in model-based decision support. Integrated Assessment, 4(1), 5–17.
  • Welde, M., & Odeck, J. (2011). Do planners get it right? The accuracy of travel demand forecasting in Norway. European Journal of Transport and Infrastructure Research, 1(11), 80–95.
  • Zhao, Y., & Kockelman, K. (2002). The propagation of uncertainty through travel demand models: An exploratory analysis. The Annals of Regional Science, 36(1), 145–163.

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