TRB 2016 Blue Ribbon Committee
16th National Transportation Planning Applications Conference

Handling Long Distance Trips in Statewide Model Peak Period Assignments

Corresponding Author: Steven Trevino, RSG

Presented By: Steven Trevino, RSG


Although long distance trips are much less common than shorter trips, because each trip has the potential to contribute so many vehicle miles of travel, these trips have a large and disproportionate effect on congestion and traffic on major intercity corridors. Moreover, a significant portion of long distance trips related to business travel also have notably higher value of time than most other trips, so reductions in delays for these trips can produce comparatively large economic benefits.

Given their significance and the various ways that the characteristics of long distance trip differ from shorter trips, long distance trips are commonly represented explicitly in statewide travel models. Some statewide models only assign traffic at a daily level, but others attempt to represent various periods of the day, given the varying levels of congestion in urban areas. In these models, some consideration must be given to the fact that long distance trips cannot be completed within the peak periods used for assignment.

The Tennessee statewide model uses the new national long distance passenger travel demand model developed by FHWA to predict long distance demand. However, the national model predicts tours and trips at an annual level, so these must be apportioned to a typical day and to periods within the day. Simple multinomial logit models were estimated using a limited sample of long distance trips from Tennessee’s add-on to the National Household Travel Survey (NHTS). These models predict the period during which a trip’s mid-point falls. Based on the dispersed unimodal distribution and relatively even distribution of long distance trip mid-points in peak periods, the problem was simplified by using a uniform distribution. With this simple approximation, it is straightforward to calculate the expected portion of a trip falling within a peak period based on its length. This calculation was used to apportion long distance trips from the national model to the peak period trip tables for assignments. Although the process involves some simplification, it provides a practical approach where dynamic traffic assignment (DTA) is not feasible for statewide models. This is believed to be the first documentation of such a method.


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