Report D – Revised Comprehensive Report: Development of Long Distance Multimodal Passenger Travel Modal Choice Model

Anderson, M. S.; Simkins, J.M.; Battelle

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ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.

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Report D – Revised Comprehensive Report: Development of Long Distance Multimodal Passenger Travel Modal Choice Model

2012-07-23
By Anderson, M. S. ; Simkins, J.M.

English

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Details:

Creators:

Anderson, M. S. ; Simkins, J.M.

Anderson, M. S. ; Simkins, J.M. Less -
Corporate Creators:

Battelle
Corporate Contributors:

United States. Federal Highway Administration. Office of Highway Policy Information
Subject/TRT Terms:

[+]

Choice Models Logistic Regression Analysis Long-Distance Travel Mode Choice Multimodal Transportation Multinomial Logistic Regression Model Passenger Travel Mode Choice Traffic Models
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Federal Highway Administration. Office of Highway Policy Information
Abstract:

This report includes an executive summary as well as details of research conducted to develop a set of statistical models to predict long-distance passenger travel mode. A literature and practice review was conducted to gather information on the current knowledge and practices for long-distance passenger travel modal choices. Using this information, a set of multinomial logistic regression models were developed to predict mode choice given various demographic and socioeconomic attributes of the traveler, trip characteristics such as length and purpose, land-use characteristics, as well as availability of transportation infrastructure. The models use long-distance travel data from the 2001 NHTS as well as other sources. K-fold cross-validation is used to assess the predictive ability of the models.
Format:

PDF
Funding:

DTFH61-07-D-00010
Collection(s):

Federal Highway Administration
Main Document Checksum:

[+]

urn:sha256:bb034f84037b732b2094f0f1819d2dca47ce73d37da7b7be4e65905f021a5d88
Download URL:

https://rosap.ntl.bts.gov/view/dot/56160/dot_56160_DS1.pdf
File Type:

[PDF-1.09 MB]