Post-Construction Evaluation of Traffic Forecast Accuracy

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. The forecast traffic data for this study is drawn from Environmental Impact Statements (EIS), Transportation Analysis Reports (TAR) and other forecast reports produced by the Minnesota Department of Transportation (Mn/DOT) with a horizon forecast year of 2010 or earlier. The actual traffic data is compiled from the database of traffic counts maintained by the Office of Traffic Forecasting & Analysis section at Mn/DOT. Based on recent research on forecast accuracy, the (in)accuracy of traffic forecasts is estimated as a ratio of the forecast traffic to the actual traffic. The estimation of forecast (in)accuracy also involves a comparison of the socioeconomic and demographic assumptions, the assumed networks to the actual in-place networks and other travel behavior assumptions that went into generating the traffic forecasts against actual conditions. The analysis indicates a general trend of underestimation in roadway traffic forecasts with factors such as highway type, functional classification, direction playing an influencing role. Roadways with higher volumes and higher functional classifications such as freeways are subject to underestimation compared to lower volume roadways/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.

[1]  M. Dix,et al.  Error and uncertainty in travel surveys , 1981 .

[2]  David J. Ashley.  Uncertainty in the context of highway appraisal , 1980 .

[3]  R. Bain,et al.  Traffic forecasting risk: study update 2004 , 2004 .

[4]  R A Johnston,et al.  TRAVEL MODELING WITH AND WITHOUT FEEDBACK TO TRIP DISTRIBUTION. TECHNICAL NOTE , 1996 .

[5]  I H MacKinder,et al.  THE PREDICTIVE ACCURACY OF BRITISH TRANSPORT STUDIES IN URBAN AREAS , 1981 .

[6]  Muriel Beser Hugosson,et al.  Quantifying uncertainties in a national forecasting model , 2005 .

[7]  R. Noland.  Relationships between highway capacity and induced vehicle travel , 2001 .

[8]  B. Flyvbjerg.  Measuring Inaccuracy in Travel Demand Forecasting: Methodological Considerations Regarding Ramp Up and Sampling , 2005, 1303.7401.

[9]  B. Flyvbjerg,et al.  Megaprojects and Risk: An Anatomy of Ambition , 2004, Perspectives on Politics.

[10]  Søren L. Buhl,et al.  How (In)accurate Are Demand Forecasts in Public Works Projects?: The Case of Transportation , 2005, 1303.6654.

[11]  Juan de Dios Ortúzar,et al.  Forecasting and data aggregation: theory and practice , 1990 .

[12]  J. Kain.  Deception in Dallas: Strategic Misrepresentation in Rail Transit Promotion and Evaluation , 1990 .

[13]  Alan Altshuler,et al.  Mega-Projects: The Changing Politics of Urban Public Investment , 2003 .

[14]  I H MacKinder.  The predictive accuracy of British transport studies , 1979 .

[15]  Marc Gaudry,et al.  An Aggregate Time-Series Analysis of Urban Transit Demand: the Montreal Case , 1975 .

[16]  R B Noland,et al.  INDUCED TRAVEL: A REVIEW OF RECENT LITERATURE AND THE IMPLICATIONS FOR TRANSPORTATION AND ENVIRONMENTAL POLICY , 2000 .

[17]  Youssef Dehghani,et al.  An investigation of prediction errors in work trip mode choice models , 1982 .

[18]  Joel L. Horowitz,et al.  Comparison of measured and forecast traffic volumes on urban interstate highways , 1978 .

[19]  Phil. Goodwin,et al.  Empirical evidence on induced traffic , 1996 .

[20]  John P. Robinson,et al.  Unlearning and backcasting: Rethinking some of the questions we ask about the future , 1988 .

[21]  Caroline J Rodier.  Verifying Accuracy of Regional Models Used in Transportation and Air Quality Planning: Case Study in Sacramento, California, Region , 2004 .

[22]  Kara M. Kockelman,et al.  The propagation of uncertainty through travel demand models: An exploratory analysis , 2000 .

[23]  M. Gendell,et al.  Older Workers: Increasing Their Labor Force Participation and Hours of Work , 2008 .

[24]  Søren L. Buhl,et al.  Inaccuracy in Traffic Forecasts , 2006 .

[25]  Jonathan E. D. Richmond,et al.  A whole-system approach to evaluating urban transit investments , 2001 .

[26]  Andrew Daly,et al.  Uncertainty in traffic forecasts: literature review and new results for The Netherlands , 2007 .

[27]  Dick Nelson,et al.  IDENTIFYING UNCERTAINTIES IN FORECASTS OF TRAVEL DEMAND , 2001 .

[28]  Martin Wachs.  Ethical Dilemmas in Forecasting for Public Policy , 1982 .

[29]  D. Pickrell.  A Desire Named Streetcar Fantasy and Fact in Rail Transit Planning , 1992 .

[30]  Hani S. Mahmassani,et al.  Uncertainty in transportation systems evaluation: issues and approaches , 1984 .

[31]  Kang-Tsung Chang,et al.  Effects of Zoning Structure and Network Detail on Traffic Demand Modeling , 2002 .

[32]  R Bain,et al.  Traffic forecasting risk study update 2005: through ramp-up and beyond , 2005 .