Transferability of Activity-Based Model Parameters

Abstract

The Strategic Highway Research Program 2 (SHRP 2) program developed proof-of-concept Dynamic Integrated Models in partnership with planning organizations in Sacramento, California, and Jacksonville, Florida. “Dynamic Integrated Model” refers to an activity-based travel demand model linked with a feedback loop to a Dynamic Traffic Assignment (simulation) model. The goal of that research was to improve urban-scale modeling and network procedures to address operations or spot improvements that affect travel-time choice, route choice, mode choice, reliability, or emissions. Building a new activity-based model set for transportation planning is an expensive and time-consuming commitment. The objective of this research was to determine if activity-based model parameters can be successfully transferred from one community to another. If transfer of parameters could be shown to produce reasonable results, it could save development time and money. DaySim, an activity-based travel demand model originally developed in Sacramento, California, was applied to Jacksonville, Florida, with Sacramento parameters and then calibrated to the Jacksonville environment. DaySim was also applied to Tampa, Florida, with Sacramento parameters and then calibrated with local data. A statistical analysis was performed to identify significant differences between transferred parameters and parameters developed from local data. Variations in model performance on validation tests were also evaluated. The analyses identified specific model components that would be better transferred than re-estimated and others for which it would be better to re-estimate. A model with borrowed parameters must still be calibrated against local conditions. A significant finding of the research was that there must be a good match between the complexity of the source model to be transferred and the depth and coverage of data available for calibrating at the destination site. A second finding was that urban areas must be similar in key demographics such as household size, age, income, auto ownership, and trip purposes. This report will be of particular interest to planning organizations considering development of an activity-based travel demand model and, in general, to professionals who use travel demand models as part of the transportation planning process.

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