Model Accuracy Data for Post-Construction Evaluation of Forecast Accuracy in Minnesota

  • David M Levinson (Creator)
  • Pavithra K Parthasarthi (Creator)

Dataset

Description

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

Transportation Data and Analysis at Mn/DOT. Based on recent research on forecast accuracy, the inaccuracy of

traffic forecasts is estimated as a ratio of the forecast traffic to the actual traffic. The estimation of forecast

inaccuracy 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, and 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.
Date made available2017
PublisherData Repository for the University of Minnesota

Cite this