Traffic Forecasting Accuracy Assessment Research (2020) / Chapter Skim
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I-54 The project team recommends that planners and engineers consider the results of past accuracy assessments in improving traffic forecasting methods. Building from that broad recommendation, this chapter describes three specific ways in which traffic forecast assessments can be used to guide method improvements.
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Improving Traffic Forecasting Methods I-55 It is logical that such a deep dive analysis would be performed before a model development project. When models are being developed, resources are already being allocated, and the results of this kind of analysis may inform and improve the allocation of those resources.
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I-56 Traffic Forecasting Accuracy Assessment Research for project-level forecasting. However, sensitivity testing is limited because it does not involve a comparison to observed data.
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Improving Traffic Forecasting Methods I-57 5.3 Large-N Analysis for Method Selection The third way that traffic forecast accuracy evaluations can be used to improve traffic forecasting methods is to use Large-N analysis to determine whether some methods produce more accurate forecasts than others. Considering alternative methods and models is useful for many situations in traffic forecasting.
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I-58 Traffic Forecasting Accuracy Assessment Research The second, and more robust mechanism for addressing the research design problem is to explicitly design the sample to control for potential confounding effects. One straightforward approach is to compare forecasts for the same project that have been made using multiple (differing)
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