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Draft Technical Documentation: San Francisco Bay Area UrbanSim Application prepared for: Metropolitan Transportation Commission (MTC) in collaboration with Association of Bay Area Governments (ABAG) March 28, 2013 Paul Waddell, Principal Investigator Urban Analytics Lab Institute of Urban And Regional Development University of California, Berkeley Acknowledgments The development of OPUS and UrbanSim has been supported by grants from the National Science Foundation Grants CMS-9818378, EIA-0090832, EIA-0121326, IIS-0534094, IIS-0705898, IIS-0964412, and IIS-0964302 and by grants from the U.S. Federal Highway Administration, U.S. Environmental Protection Agency, European Research Council, Maricopa Association of Governments, Puget Sound Regional Council, Oahu Metropolitan Planning Organization, Lane Council of Governments, Southeast Michigan Council of Governments, Metropolitan Transportation Commis- sion and the contributions of many users. This application of UrbanSim to the San Francisco Bay Area has been funded by the Metropolitan Transportation Commission (MTC). The UrbanSim Development and Application Team UrbanSim is an urban simulation system designed by Paul Waddell, and developed over a number of years with the effort of many individuals working towards common aims. See the UrbanSim People page for current and previous contributors, at www.urbansim.org/people. The following persons participated in the development of the UrbanSim Application to the San Francisco Bay Area: Paul Waddell, City and Regional Planning, University of California Berkeley (Principal Investigator) Ian Carlton, City and Regional Planning, University of California Berkeley Brian Cavagnolo, City and Regional Planning, University of California Berkeley Regina Clewlow, City and Regional Planning, University of California Berkeley Federico Fernandez, City and Regional Planning, University of California Berkeley Fletcher Foti, City and Regional Planning, University of California Berkeley Conor Henley, City and Regional Planning, University of California Berkeley Eddie Janowicz, City and Regional Planning, University of California Berkeley Hyungkyoo Kim, City and Regional Planning, University of California Berkeley Aksel Olsen, City and Regional Planning, University of California Berkeley Pedro Peterson, City and Regional Planning, University of California Berkeley Carlos Vanegas, City and Regional Planning, University of California Berkeley David Von Stroh, City and Regional Planning, University of California Berkeley Liming Wang, Institute for Urban and Regional Development, University of California Berkeley David Weinzimmer, City and Regional Planning, University of California Berkeley UrbanSim Home Page: www.urbansim.org Collaboration with MTC and ABAG Staff This project has been done in close collaboration with the staff of the Metropolitan Transportation Commission (MTC) and of the Association of Bay Area Governments (ABAG). In particular, we wish to acknowledge the leadership of Ashley Nguyen, the Project Manager for this effort at MTC before turning these duties over to Carolyn Clevenger, as well as the tireless help of Mike Reilly at ABAG, and David Ory at MTC. Many other staff at MTC and at ABAG have participated in the development of the data, the scenarios and the analysis described in this report. i CONTENTS 1 Introduction and Overview of UrbanSim 1 1.1 Introduction . .1 1.1.1 Bay Area Model Application Project . .1 1.1.2 Intended Uses of the Model System . .1 1.1.3 Assumptions and Limitations of the Model System . .2 1.2 UrbanSim Overview . .3 1.2.1 Design Objectives and Key Features . .3 1.2.2 Model System Design . .5 1.2.3 Policy Scenarios . .8 1.2.4 Discrete Choice Models . .9 2 Bay Area UrbanSim Models 12 2.1 Business Transition Model . 12 2.1.1 Objective . 12 2.1.2 Algorithm . 12 2.1.3 Configuration . 14 2.1.4 Data . 14 2.2 Household Transition Model . 14 2.2.1 Objective . 14 2.2.2 Algorithm . 15 2.2.3 Configuration . 15 2.2.4 Data . 15 2.3 Business Relocation Model . 16 2.3.1 Objective . 16 2.3.2 Algorithm . 16 2.3.3 Configuration . 17 2.3.4 Data . 17 2.4 Household Relocation Model . 17 2.4.1 Objective . 17 2.4.2 Algorithm . 18 2.4.3 Configuration . 18 2.4.4 Data . 18 2.5 Household Tenure Choice Model . 19 2.5.1 Objective . 19 2.5.2 Algorithm . 19 2.5.3 Configuration . 19 2.5.4 Data . 19 2.6 Business Location Choice Model . 19 2.6.1 Objective . 19 ii 2.6.2 Algorithm . 21 2.6.3 Configuration . 21 2.6.4 Data . 22 2.7 Household Location Choice Model . 22 2.7.1 Objective . 22 2.7.2 Algorithm . 24 2.7.3 Configuration . 25 2.7.4 Data . 25 2.8 Real Estate Price Model . 25 2.8.1 Objective . 25 2.8.2 Hedonic Price Regression . 26 Algorithm . 26 Configuration . 26 Data................................................ 27 2.8.3 Market Price Equilibration . 27 2.9 Real Estate Developer Model . 28 2.9.1 Objective . 28 2.9.2 Algorithm . 28 2.9.3 Data . 29 2.10 Government and Schools Allocation . 30 2.10.1 Objective . 30 2.10.2 Algorithm . 30 2.11 The Role of Accessibility . 31 2.12 User-Specified Events . 31 3 Model Data Structures 32 3.1 annual_business_control_totals . 32 3.2 annual_household_control_totals . 33 3.3 annual_household_relocation_rates . 33 3.4 annual_business_relocation_rates . 34 3.5 buildings . 34 3.6 building_sqft_per_job . 42 3.7 building_types . 42 3.8 employment_sectors . 42 3.9 households . 43 3.10 establishments . 46 3.11 parcels . ..
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