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Page 122
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Traffic Forecasting Accuracy Assessment Research. Washington, DC: The National Academies Press. doi: 10.17226/25637.
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Page 123
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Traffic Forecasting Accuracy Assessment Research. Washington, DC: The National Academies Press. doi: 10.17226/25637.
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Page 123
Page 124
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Traffic Forecasting Accuracy Assessment Research. Washington, DC: The National Academies Press. doi: 10.17226/25637.
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Page 124

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

II-48 References Andersson, M., Brundell-Freij, K., and Eliasson, J. (2017). “Validation of Aggregate Reference Forecasts for Passenger Transport.” Transportation Research Part A: Policy and Practice, 96(Supplement C), 101–118. Australian Government. (2012). Addressing Issues in Patronage Forecasting for PPP/Toll Roads. Department of Infrastructure, Regional Development and Cities, Canberra, Australia. Bain, R. (2009). “Error and Optimism Bias in Toll Road Traffic Forecasts.” Transportation, 36(5): 469–82. https://doi.org/10.1007/s11116-009-9199-7. Bain, R. (2011a). “On the Reasonableness of Traffic Forecasts.” TEC Magazine. Bain, R. (2011b). “The Reasonableness of Traffic Forecasts Findings from a Small Survey.” Traffic Engineering and Control (TEC) Magazine. Bain, R. (2013). “Toll Roads: Big Trouble Down Under.” Infrastructure Journal. Bain, R., and L. Polakovic (2005). “Traffic forecasting risk study update 2005: through ramp-up and beyond.” Standard & Poor’s, London. Buck, K., and M. Sillence (2014). “A Review of the Accuracy of Wisconsin’s Traffic Forecasting Tools.” Presented at 93d Annual Meeting of the Transportation Research Board, Washington, D.C. Byram, M. (2015). “Forecasts Accuracy of Certified Traffic for Design.” Presentation to the Ohio Department of Transportation Task Force, December 2015. Cade, B. S., and B. R. Noon (2003). “A Gentle Introduction to Quantile Regression for Ecologists.” Frontiers in Ecology and the Environment, 1(8), 412–420. FHWA (2018). Traffic Data Computation Method Pocket Guide. U.S. Department of Transportation, Washington, D.C. Flyvbjerg, B. (2005). “Measuring Inaccuracy in Travel Demand Forecasting: Methodological Considerations Regarding Ramp up and Sampling.” Transportation Research, Part A: Policy and Practice, 39(6), 522–530. Flyvbjerg, B., S. K. M. Holm, and S. L. Buhl (2006). “Inaccuracy in Traffic Forecasts.” Transport Reviews, 26(1). Giaimo, G., and M. Byram (2013). “Improving Project Level Traffic Forecasts by Attacking the Problem from all Sides.” Columbus, OH. Gomez, J., J. M. Vassallo, and I. Herraiz (2016). “Explaining light vehicle demand evolution in interurban toll roads: a dynamic panel data analysis in Spain.” Transportation, 43(4), 677–703. Hartgen, D. T. (2013). “Hubris or Humility? Accuracy Issues for the Next 50 Years of Travel Demand Modeling.” Transportation, 40(6), 1133–1157. Highways England (2015). Post Opening Project Evaluation: M6 Carlisle to Guards Mill Improvement. 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. Kriger, D., S. Shiu, and S. Naylor (2006). Estimating Toll Road Demand and Revenue. Synthesis of Highway Practice, Transportation Research Board. Lemp, J., and K. Kockelman (2009). “Understanding and Accommodating Risk and Uncertainty in Toll Road Projects.” Transportation Research Record: Journal of the Transportation Research Board, 2132, 106–112. Li, Z., and D. A. Hensher (2010). “Toll Roads in Australia: An Overview of Characteristics and Accuracy of Demand Forecasts.” Transport Reviews, 30(5), 541–569. Miller, J. S., S. Anam, J. W. Amanin, and R. A. Matteo (2016). A Retrospective Evaluation of Traffic Forecasting Techniques. Virginia Transportation Research Council. Nicolaisen, M. S. (2012). Forecasts: Fact or Fiction? Uncertainty and Inaccuracy in Transport Project Evaluation. PhD thesis, Aalborg University, Aalborg, Denmark. Nicolaisen, M. S., and P. A. Driscoll (2014). “Ex-Post Evaluations of Demand Forecast Accuracy: A Literature Review.” Transport Reviews, 34(4), 540–557.

References II-49 Nicolaisen, M. S., and P. Naess (2015). “Roads to Nowhere: The Accuracy of Travel Demand Forecasts for Do-Nothing Alternatives.” Transport Policy, 37(0). https://trid.trb.org/view/2015/C/1334458. Odeck, J., and M. Welde (2017). “The Accuracy of Toll Road Traffic Forecasts: An Econometric Evaluation.” Transportation Research, Part A: Policy and Practice, 101, 73–85. Parthasarathi, P., and D. Levinson (2010). “Post-Construction Evaluation of Traffic Forecast Accuracy.” Transport Policy, 17(6), 428–443. Pedersen, N. J., and D. R. Samdahl (1982). NCHRP Report 255: Highway Traffic Data for Urbanized Area Project Planning and Design. TRB, National Research Council, Washington, D.C. Pereira, F. C., C. Antoniou, J.A. Fargas, and M. Ben-Akiva (2014). “A Metamodel for Estimating Error Bounds in Real-Time Traffic Prediction Systems.” IEEE Transactions on Intelligent Transportation Systems, 15(3), 1310–1322. Tsai, C.-H. P., C. Mulley, and G. Clifton (2014). “Forecasting Public Transport Demand for the Sydney Greater Metropolitan Area: A comparison of Univariate and Multivariate Methods.” Road & Transport Research: A Journal of Australian and New Zealand Research and Practice, 23(1): 51. U.S. DOT (n.d.). “Fixing America’s Surface Transportation Act or ‘FAST Act.’” Federal Highway Administration, Washington, D.C. Webpage: https://www.fhwa.dot.gov/fastact/funding.cfm (accessed October 6, 2016). Welde, M., and J. Odeck (2011). “Do Planners Get it Right? The Accuracy of Travel Demand Forecasting in Norway.” EJTIR, 1(11): 80–95. Zhang, X., and M. Chen (2019). “Quantifying the Impact of Weather Events on Travel Time and Reliability,” Journal of Advanced Transportation. https://doi.org/10.1155/2019/8203081.

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 Traffic Forecasting Accuracy Assessment Research
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Accurate traffic forecasts for highway planning and design help ensure that public dollars are spent wisely. Forecasts inform discussions about whether, when, how, and where to invest public resources to manage traffic flow, widen and remodel existing facilities, and where to locate, align, and how to size new ones.

The TRB National Cooperative Highway Research Program's NCHRP Report 934: Traffic Forecasting Accuracy Assessment Research seeks to develop a process and methods by which to analyze and improve the accuracy, reliability, and utility of project-level traffic forecasts.

The report also includes tools for engineers and planners who are involved in generating traffic forecasts, including: Quantile Regression Models, a Traffic Accuracy Assessment, a Forecast Archive Annotated Outline, a Deep Dive Annotated Outline, and Deep Dive Assessment Tables,

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