The changing accuracy of traffic forecasts

Jawad Mahmud Hoque, Gregory D. Erhardt, David Schmitt, Mei Chen, Ankita Chaudhary, Martin Wachs, Reginald R. Souleyrette

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy—traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time: more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.

Original languageEnglish
Pages (from-to)445-466
Number of pages22
JournalTransportation
Volume49
Issue number2
DOIs
StatePublished - Apr 2022

Bibliographical note

Funding Information:
This research was funded through the Cooperative Research Programs of the Transportation Research Board.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

Keywords

  • Forecast accuracy
  • Induced demand
  • Traffic forecasting
  • Travel demand modeling

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Development
  • Transportation

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