Estimating Through-Trip Travel without External Surveys

Because through trips can be a significant portion of travel in a study area, estimating them is an important part of travel demand modeling. In the past through trips were often estimated by using external surveys. External surveys were recently suspended in Texas, so Texas transportation planners...

Full description

Saved in:
Bibliographic Details
Published inTransportation research record Vol. 2254; no. 1; pp. 104 - 111
Main Authors Talbot, Eric S., Burris, Mark W., Farnsworth, Steve
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.01.2011
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Because through trips can be a significant portion of travel in a study area, estimating them is an important part of travel demand modeling. In the past through trips were often estimated by using external surveys. External surveys were recently suspended in Texas, so Texas transportation planners need a way to estimate through trips without using external surveys. Previous research has focused on study areas with populations of less than 200,000, but many Texas study areas have populations of more than 200,000. This research developed a set of two logit models to estimate through trips for a wide range of study area sizes. The first model estimates the portion of all trips at an external station that are through trips. The second model estimates the external stations at which the trips originated. The models produce separate results for commercial and noncommercial vehicles, and these results can be used to develop through-trip tables. For predictor variables, the models use results from a simple gravity model, the average daily traffic at each external station as a proportion of the total average daily traffic at all external stations, the number of turns on the routes between external station pairs, and whether the route passes through the study area and does not pass through any other external stations. Evaluations of the models’ performance showed that the predictions fit the observations reasonably well, indicating that the models can be useful for practical applications.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0361-1981
2169-4052
DOI:10.3141/2254-11