Traffic Forecasting Accuracy Assessment Research (2020) / Chapter Skim
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Pages 81-93
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From page 81... ...
II-7 Large-N Analysis 2.1 Introduction to Large-N Analysis The assessment of traffic forecasting accuracy in NCHRP 08-110 builds upon past efforts. Several researchers have assessed the accuracy of traffic forecasts, although most of the research projects have focused on toll roads.
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II-8 Traffic Forecasting Accuracy Assessment Research projects in Virginia, Miller et al.
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From page 83... ...
Large-N Analysis II-9 A segment is a unique portion of roadway for which a forecast is provided. The forecasts for an interchange improvement project may thus contain separate segment-level estimates for both directions of the freeway, for both directions of the crossing arterial, and for each ramp.
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II-10 Traffic Forecasting Accuracy Assessment Research To ensure fair comparisons, the count units and the forecast units should be the same. Commonly used count units include: • Average Daily Traffic (ADT)
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Large-N Analysis II-11 From the database and project reports, however, it became apparent to the project team that traffic forecasts are usually done for three analysis years: 1. The opening year, 2.
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II-12 Traffic Forecasting Accuracy Assessment Research time the project decision is made (whereas the actual volume is not known until much later)
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Large-N Analysis II-13 observations, the average PDFF could be expected to be roughly the same. There would be a difference, however, in the measured t-statistics, wherein the larger sample size from a segmentlevel analysis could suggest significance where a project level analysis would not.
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From page 88... ...
II-14 Traffic Forecasting Accuracy Assessment Research where yi = the actual traffic on Project i, ŷi = the forecast traffic on Project i, ei = a random error term, α and β = estimated terms in the regression, and here α = 0 and β = 1 implies unbiasedness. Li and Hensher (2010)
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From page 89... ...
Large-N Analysis II-15 2.3 Results 2.3.1 Overall Distribution Generally speaking, traffic forecasts have been found to be overpredicting: actual traffic volumes after project completion are lower than what has been forecast, as shown by the rightskewed distribution in Figure II-1. The 3,911 unique records/segments in the database reflected 1,291 unique projects.
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II-16 Traffic Forecasting Accuracy Assessment Research understandable, since the percentages were taken as a ratio over the forecast volume. Unless the actual traffic differs by a large margin, the PDFF values will not have risen to a big amount.
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From page 91... ...
Large-N Analysis II-17 2.4 Quantile Regression Results The uncertainties involved in forecasting traffic call for assessing the risks and subsequently developing a range of forecasts of the traffic volumes that can be expected on a project. Considering the forecast accuracy dataset to be representative (i.e., a "national average")
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II-18 Traffic Forecasting Accuracy Assessment Research Table II-6 presents the regression statistics (coefficients or α and β values and the t value to assess the significance)
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Large-N Analysis II-19 Applying the coefficients as an equation, the project team constructed ranges of actual traffic and PDFF for differing forecast volumes (Figure II-3)
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