Traffic Forecasting Accuracy Assessment Research (2020) / Chapter Skim
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III-D-1 Forecast Card Data Assumptions A P P E N D I X D Understandably, the organization, clarity, and detail of the available information varied across the historical datasets used to create the initial forecast accuracy database and the subsequent Forest Cards and Forest Card Data repository. In most cases, some assumptions were made.
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III-D-2 Traffic Forecasting Accuracy Assessment Research Some of the assumptions made for the Florida D4 dataset are as follows: 1. The date of the report is assumed to be same as the year when the forecast was completed.
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Appendix D: Forecast Card Data Assumptions III-D-3 2 Michigan The Michigan dataset was provided by the Michigan DOT in the form of both PDF reports and an Excel table. Whenever a mismatch occurred between the information in the reports and the Excel table, the information in the reports was considered legitimate.
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III-D-4 Traffic Forecasting Accuracy Assessment Research 3. For TAR# 2293, multiple forecasts exist for the same segment.
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Appendix D: Forecast Card Data Assumptions III-D-5 Some of the assumptions made in the Minnesota dataset are as follows: 1. Records with no or zero value for the Forecast AADT were removed from the dataset.
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III-D-6 Traffic Forecasting Accuracy Assessment Research Table III-D-5. Wisconsin field descriptions.
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Appendix D: Forecast Card Data Assumptions III-D-7 4. For built projects, the assumed method for forecasting is using the Regional Travel Demand Model only.
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