Transferability of Activity-Based Model Parameters (2014)

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TRANSPORTATION RESEARCH BOARD WASHINGTON, D.C. 2014 www.TRB.org The Second S T R A T E G I C H I G H W A Y R E S E A R C H P R O G R A M REPORT S2-C10A-RW-2 Transferability of Activity-Based Model Parameters John Gliebe, Mark bradley, nazneen Ferdous, Maren outwater, haiyun lin, and Jason Chen RSG White River Junction, Vermont

Subject Areas Environment Highways Planning and Forecasting

The Second Strategic Highway Research Program America’s highway system is critical to meeting the mobility and economic needs of local communities, regions, and the nation. Developments in research and technology—such as advanced materials, communications technology, new data collection tech- nologies, and human factors science—offer a new opportunity to improve the safety and reliability of this important national resource. Breakthrough resolution of significant transportation problems, however, requires concentrated resources over a short time frame. Reflecting this need, the second Strategic Highway Research Program (SHRP 2) has an intense, large-scale focus, integrates multiple fields of research and technology, and is fundamentally different from the broad, mission-oriented, discipline-based research programs that have been the mainstay of the highway research industry for half a century. 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SHRP 2 focuses on applied research in four areas: Safety, to prevent or reduce the severity of highway crashes by understanding driver behavior; Renewal, to address the aging infrastructure through rapid design and construction methods that cause minimal disruptions and produce lasting facilities; Reliability, to reduce congestion through incident reduction, management, response, and mitigation; and Capacity, to integrate mobility, economic, environmental, and community needs in the planning and designing of new trans- portation capacity. SHRP 2 was authorized in August 2005 as part of the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (SAFETEA-LU). The program is managed by the Transportation Research Board (TRB) on behalf of the National Research Council (NRC). 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ACKNOWLEDGMENTS This work was sponsored by the Federal Highway Administration in cooperation with the American Asso- ciation of State Highway and Transportation Officials. It was conducted in the second Strategic Highway Research Program (SHRP 2), which is administered by the Transportation Research Board of the National Academies. The project was managed by Stephen J. Andrle, Deputy Director for SHRP 2. Jason Chen and Haiyun Lin were the RSG staff members who performed most of the technical work described in this document. They received scripting and GIS support from Bhargava Sana and Erich Rentz, respectively. Joe Wildey provided copy editing and formatting support for this report. The work done to create synthetic populations was led by the Fulton School of Engineering at Arizona State University. John Bowman was responsible for much of the work referenced in Appendix C on the transferability of estimated parameters. This work would not have been possible without the cooperation and hard work of the staff members of the North Florida Transportation Planning Organization in Jacksonville and the District 7 Systems Planning group of the Florida Department of Transportation, Tampa. These agencies were supported by teams of local consultants: Atkins; Gannett Fleming, Inc.; Grimail Crawford Inc.; and Reynolds, Smith & Hill. SHRP 2 STAFF Ann M. Brach, Director Stephen J. Andrle, Deputy Director Neil J. Pedersen, Deputy Director, Implementation and Communications Cynthia Allen, Editor Kenneth Campbell, Chief Program Officer, Safety JoAnn Coleman, Senior Program Assistant, Capacity and Reliability Eduardo Cusicanqui, Financial Officer Richard Deering, Special Consultant, Safety Data Phase 1 Planning Walter Diewald, Senior Program Officer, Safety Shantia Douglas, Senior Financial Assistant Charles Fay, Senior Program Officer, Safety Carol Ford, Senior Program Assistant, Renewal and Safety Jo Allen Gause, Senior Program Officer, Capacity Rosalind Gomes, Accounting/Financial Assistant James Hedlund, Special Consultant, Safety Coordination Alyssa Hernandez, Reports Coordinator Ralph Hessian, Special Consultant, Capacity and Reliability Andy Horosko, Special Consultant, Safety Field Data Collection William Hyman, Senior Program Officer, Reliability Linda Mason, Communications Officer Reena Mathews, Senior Program Officer, Capacity and Reliability Matthew Miller, Program Officer, Capacity and Reliability Michael Miller, Senior Program Assistant, Capacity and Reliability David Plazak, Senior Program Officer, Capacity Rachel Taylor, Senior Editorial Assistant Dean Trackman, Managing Editor Connie Woldu, Administrative Coordinator

F O R E W O R D Stephen J. Andrle, SHRP 2 Deputy Director 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. The SHRP 2 program devel- oped proof-of-concept Dynamic Integrated Models in partnership with planning organi- zations 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 develop- ment 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 cali- brated to the Jacksonville environment. DaySim was also applied to Tampa, Florida, with Sacramento parameters and then calibrated with local data. A statistical analysis was per- formed 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 trans- ferred than reestimated and others for which it would be better to reestimate. 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. Tampa has a much higher proportion of retirees and non-work-trip purposes than either Sacramento or Jacksonville, a situation that affected the transferability of parameters. Travel demand models have been used for more than half a century to determine the need and estimate the usage of proposed new highway and transit systems. The majority of such models use Traffic Analysis Zones to aggregate demographic data and estimate interzonal travel demand for large time blocks (such as morning peak period). The interzonal demand is assigned to a link and node network to estimate likely roadway volumes. Activity-based travel demand models are based on the disaggregate travel activity of indi- vidual travelers, not the aggregate behavior of all the travelers in a zone. They have the poten- tial to better simulate behaviors such as time-of-day choice, route choice, mode choice, and trip chaining. Because they are disaggregate and based on individual behavior, there may be potential to borrow model structures and parameters to reduce model development costs in new locations.

In this project the DaySim activity-based demand model developed in Sacramento, California, was transferred to both the Jacksonville and Tampa, Florida, regions. The struc- ture and parameters (coefficients) of the original Sacramento DaySim model were applied in Jacksonville and Tampa using local demographic and land-use data. Then, local data were used to reestimate parameters and coefficients, effectively creating new activity-based model sets for the Jacksonville and Tampa regions. Statistical and model performance tests were conducted between the model pairs, revealing significant differences that varied by model component and the regions being compared. The analysis was hampered by small sample sizes or absence of data for certain variables required in the Sacramento DaySim specifications, leading to the observation that the com- plexity of a borrowed model specification should be supported by the data available at the destination site. In addition, spatial distribution of activity centers is region specific, which can lead to differences in mean trip lengths.

C O N T E N T S 1 Executive Summary 3 CHAPTER 1 Background 3 Motivation for the Study 3 Overview of the Study 4 Assessing Transferability 4 Confounding Factors 6 CHAPTER 2 Research Approach 6 Data Development and Integration 6 Parcel-Based Land-Use Data 7 Regional Households and Employment 8 Network Models 9 Auxiliary Demand Models 10 Urban Form and Accessibility Variables 10 Model Estimation 10 Model Calibration 12 CHAPTER 3 Findings and Applications 12 Estimation of Model Components to Test Transferability 12 Transferability Tests for Tampa and Jacksonville 24 Calibration of Regional Models to Test Transferability 29 CHAPTER 4 Conclusions 29 Reestimation Tests 30 Calibration Tests 31 Final Recommendations 32 References 33 Appendix A. Detailed Model Estimation Results 110 Appendix B. Summary of Model Calibration Differences 133 Appendix C. Transferability Tests for Six Regions