Best practical experience model standard in project-level traffic forecasting
This page is open for editing because it is part of the Incubator. Have something to add? Please register so you can contribute. Have an option you would like to share? Please click on the 'Talk' button to enter the dialogue. The TF Resource Volunteers appreciate your feedback and interest.
The “best practical experience model” is a specification of a travel model that can be used for project-level forecasts, with or without the need for a refinement step. The “best practical experience model” uses off-the-shelf technology, but adheres fairly closely to the travel model ideal. The specifications listed below cover highway forecasts, exclusively:
- The ability to estimate demands between all origins and all destinations through behavioral principles, through an O-D table estimated with traffic counts, or both;
- The ability to make adjustments to the O-D table to reflect differences between base-year traffic counts and base-year forecasted volumes;
- The ability to perform dynamic equilibrium traffic assignments, with appropriate feedback to earlier steps, if necessary;
- The ability to calculate delays for through and turning movements (separately) at traffic controlled intersections according to accepted traffic engineering principles, such as operational analysis procedures from the “2010 Highway Capacity Manual”;
- The ability to incorporate delays from turning movements into traffic assignments;
- The ability to apply time-of-day (TOD) factors prior to traffic assignment for peak-hour assignments;
- The ability to handle a fine-grained zone system;
- The ability to handle a high level of network detail, including streets of functional classes lower than minor arterial;
- The ability to have multiple vehicle classes to correctly track trucks;
- The ability to have multiple driver classes to correctly represent the effects road pricing has on path choice. (Adapted from the Travel Model Ideal, NCHRP Report 765).
The “best practical experience model” should be capable of obtaining validation statistics close to those in the second column of the Table in Quality assurance and validation standards, which come from a region in the US that is using a similarly constructed model.