Integration of National Long-Distance Passenger Travel Demand Model with Tennessee Statewide Model and Calibration to Big Data

Author:

Bernardin Vincent L.1,Ferdous Nazneen2,Sadrsadat Hadi3,Trevino Steven1,Chen Chin-Cheng4

Affiliation:

1. RSG, 2709 Washington Avenue, Suite 9, Evansville, IN 47714

2. CH2M, 2411 Dulles Corner Park, Suite 500, Herndon, VA 20171

3. RSG, 2200 Wilson Boulevard, Suite 205, Arlington, VA 22201

4. Tennessee Department of Transportation, James K. Polk Building, 505 Deaderick Street, Suite 900, Nashville, TN 37243-0334

Abstract

The Tennessee Department of Transportation replaced the quick-response-based long-distance component in its statewide model by integrating the new national long-distance passenger travel demand model in a new statewide model and calibrating it to long-distance trips observed in cell phone origin–destination data. The national long-distance model is a tour-based simulation model developed from FHWA research on long-distance travel behavior and patterns. The tool allows the evaluation of many policy scenarios, including fare or service changes for various modes, such as commercial air, intercity bus, Amtrak rail, and highway travel. The availability of this tool presents an opportunity for state departments of transportation in developing statewide models. Commercial big data from cell phones for long-distance trips also pre-sents an opportunity and a new data source for long-distance travel patterns, which previously have been the subject of limited data collection, in the form of surveys. This project is the first to seize on both of these opportunities by integrating the national long-distance model with the new Tennessee statewide model and by processing big data for use as a calibration target for long-distance travel in a statewide model. The paper demonstrates the feasibility of integrating the national model with statewide models, the ability of the national model to be calibrated to new data sources, the ability to combine multiple big data sources, and the value of big data on long-distance travel, as well as important lessons on its expansion.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference13 articles.

1. Long-Distance and Rural Travel Transferable Parameters for Statewide Travel Forecasting Models

2. BernardinV., RentzE., and GradyB. TMIP How-To: Create Travelshed TAZs. Travel Model Improvement Program, FHWA, U.S. Department of Transportation, 2015.

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