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Post-construction evaluation of traffic forecast accuracy

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  • Parthasarathi, Pavithra
  • Levinson, David

Abstract

This research evaluates the accuracy of demand forecasts using a sample of recently-completed projects in Minnesota and identifies the factors influencing the inaccuracy in forecasts. Based on recent research on forecast accuracy, the inaccuracy of traffic forecasts is estimated as the difference between forecast traffic and actual traffic, standardized by the actual traffic. The analysis indicates a general trend of underestimation in roadway traffic forecasts with factors such as roadway type, functional classification and direction playing an influencing role. Roadways with higher volumes and higher functional classifications such as freeways are underestimated compared to lower volume roadways and lower functional classifications. The comparison of demographic forecasts shows a trend of overestimation while the comparison of travel behavior characteristics indicates a lack of incorporation of fundamental shifts and societal changes.

Suggested Citation

  • Parthasarathi, Pavithra & Levinson, David, 2010. "Post-construction evaluation of traffic forecast accuracy," Transport Policy, Elsevier, vol. 17(6), pages 428-443, November.
  • Handle: RePEc:eee:trapol:v:17:y:2010:i:6:p:428-443
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    Citations

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    Cited by:

    1. Vij, Akshay & Walker, Joan L., 2014. "Preference endogeneity in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 90-105.
    2. Eliasson, Jonas & Börjesson, Maria & van Amelsfort, Dirk & Brundell-Freij, Karin & Engelson, Leonid, 2013. "Accuracy of congestion pricing forecasts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 34-46.
    3. Andersson, Matts & Brundell-Freij, Karin & Eliasson, Jonas, 2017. "Validation of aggregate reference forecasts for passenger transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 101-118.
    4. Xu, Xiangdong & Chen, Anthony & Wong, S.C. & Cheng, Lin, 2015. "Selection bias in build-operate-transfer transportation project appraisals," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 245-251.
    5. Sanko, Nobuhiro & Morikawa, Takayuki & Nagamatsu, Yoshitaka, 2013. "Post-project evaluation of travel demand forecasts: Implications from the case of a Japanese railway," Transport Policy, Elsevier, vol. 27(C), pages 209-218.
    6. Maria Börjesson & Jonas Eliasson & Mattias Lundberg, 2014. "Is CBA Ranking of Transport Investments Robust?," Journal of Transport Economics and Policy, University of Bath, vol. 48(2), pages 189-204, May.
    7. Nicolaisen, Morten Skou & Næss, Petter, 2015. "Roads to nowhere: The accuracy of travel demand forecasts for do-nothing alternatives," Transport Policy, Elsevier, vol. 37(C), pages 57-63.
    8. Pavithra Parthasarathi & David Levinson & Hartwig Hochmair, 2012. "Network Structure and Travel Time Perception," Working Papers 000102, University of Minnesota: Nexus Research Group.
    9. Salling, Kim Bang & Leleur, Steen, 2015. "Accounting for the inaccuracies in demand forecasts and construction cost estimations in transport project evaluation," Transport Policy, Elsevier, vol. 38(C), pages 8-18.
    10. Morten Skou Nicolaisen & Patrick A. Driscoll, 2016. "An International Review of Ex-Post Project Evaluation Schemes in the Transport Sector," Journal of Environmental Assessment Policy and Management (JEAPM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 1-33, March.
    11. Manzo, Stefano & Nielsen, Otto Anker & Prato, Carlo Giacomo, 2015. "How uncertainty in input and parameters influences transport model :output A four-stage model case-study," Transport Policy, Elsevier, vol. 38(C), pages 64-72.
    12. Odeck, James, 2013. "How accurate are national road traffic growth-rate forecasts?—The case of Norway," Transport Policy, Elsevier, vol. 27(C), pages 102-111.
    13. Andersson, Matts & Brundell-Freij, Karin & Eliasson, Jonas, 2016. "Validation of reference forecasts for passenger transport," Working papers in Transport Economics 2016:15, CTS - Centre for Transport Studies Stockholm (KTH and VTI), revised 07 Jul 2016.

    More about this item

    Keywords

    Transportation demand forecasting Project evaluation Forecast accuracy Model evaluation;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement

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