DOCSLIB.ORG

Urbansim Application

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Urbansim Application 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 . ..
Load more

Recommended publications
  • An Examination of Land Use Models, Emphasizing Urbansim, TELUM, and Suitability Analysis
    Technical Report Documentation Page 1. Report No. 2. Government 3. Recipient’s Catalog No. FHWA/TX-09/0-5667-1 Accession No. 4. Title and Subtitle 5. Report Date An Examination of Land Use Models, Emphasizing UrbanSim, October 31, 2008 TELUM, and Suitability Analysis 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Kara Kockelman, Jennifer Duthie, Siva Karthik Kakaraparthi, 0-5667-1 Bin (Brenda) Zhou, Ardeshir Anjomani, Sruti Marepally, and Krishna Priya Kunapareddychinna 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) Center for Transportation Research 11. Contract or Grant No. The University of Texas at Austin 0-5667 3208 Red River, Suite 200 Austin, TX 78705-2650 12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered Texas Department of Transportation Technical Report Research and Technology Implementation Office September 2006-August 2008 P.O. Box 5080 Austin, TX 78763-5080 14. Sponsoring Agency Code 15. Supplementary Notes Project performed in cooperation with the Texas Department of Transportation and the Federal Highway Administration. 16. Abstract This work provides integrated transportation land use modeling guidance to practitioners in Texas regions of all sizes. The research team synthesized existing land use modeling experiences from MPOs across the country, examined the compatibility of TELUM’s and UrbanSim’s requirements with existing data sets, integrated both UrbanSim and a gravity-based land use modeling with an existing travel demand model (TDM), and examined the results of Waco and Austin land use model runs (with and without transportation and land use policies in place). A simpler, GIS-based land use suitability analysis was also performed, for Waco, to demonstrate the potential value of such approaches.
    [Show full text]
  • Architecture for Modular Microsimulation of Real Estate Markets and Transportation∗
    Architecture for Modular Microsimulation of Real Estate Markets and Transportation∗ Paul Waddell1, Ignacio Garcia-Dorado2, Samuel M. Maurer1, Geoff Boeing1, Max Gardner3, Emily Porter3, and Daniel Aliaga4 1Department of City and Regional Planning, University of California, Berkeley 2Google Research 3Department of Civil and Environmental Engineering, University of California, Berkeley 4Department of Computer Science, Purdue University June 2018 Abstract Integrating land use, travel demand, and traffic models represents a gold standard for regional planning, but is rarely achieved in a meaning- ful way, especially at the scale of disaggregate data. In this paper, we present a new architecture for modular microsimulation of urban land use, travel demand, and traffic assignment. UrbanSim is an open-source microsimulation platform used by metropolitan planning organizations worldwide for modeling the growth and development of cities over long (∼30 year) time horizons. ActivitySim is an agent-based modeling platform that produces synthetic origin–destination travel demand data, developed from the UrbanSim model and software framework. For traffic assignment, we have integrated two approaches. The first is a static user equilibrium approach that is used as a benchmark. The second is a traffic microsim- arXiv:1807.01148v1 [cs.CY] 30 Jun 2018 ulation approach that we have highly parallelized to run on a GPU in order to enable full-model microsimulation of agents through the entire modeling workflow. This paper introduces this research agenda, describes this project’s achievements so far in developing this modular platform, and outlines further research. ∗Paper presented at the Symposium on Applied Urban Modelling. Cambridge, England. June 27–29, 2018. 1 1 Introduction 1.1 Need for modular urban microsimulation Integrated urban models have a long history and uneven results.
    [Show full text]
  • Sketch Tools for Regional Sustainability Scenario Planning
    Acknowledgments This study was conducted for the AASHTO Standing Committee on Planning, with funding provided through the National Cooperative Highway Research Program (NCHRP) Project 08-36, Research for the AASHTO Standing Committee on Planning. The NCHRP is supported by annual voluntary contributions from the state Departments of Transportation. Project 08-36 is intended to fund quick response studies on behalf of the Standing Committee on Planning. The report was prepared by Uri Avin of the National Center for Smart Growth (NCSG), University of Maryland, with Christopher Porter and David von Stroh of Cambridge Systematics, Eli Knaap of the NCSG, and Paul Patnode, NCSG Affiliate. The work was guided by a technical working group that included: Robert Balmes, Michigan Department of Transportation, Chair; William Cesanek, CDM Smith; Robert Deaton, North Carolina Department of Transportation; Thomas Evans; Kristen Keener-Busby, Urban Lands Institute, Arizona; Amanda Pietz, Oregon Department of Transportation; Elizabeth Robbins, Washington State Department of Transportation; Nicolas Garcia, Liaison, Federal Transit Administration; and Fred Bowen, Liaison, Federal Highway Administration. The project was managed by Lori L. Sundstrom, NCHRP Senior Program Officer. Disclaimer The opinions and conclusions expressed or implied are those of the research agency that performed the research and are not necessarily those of the Transportation Research Board or its sponsoring agencies. This report has not been reviewed or accepted by the Transportation
    [Show full text]
  • A Primer for Agent-Based Simulation and Modeling in Transportation Applications
    The Exploratory Advanced Research Program A Primer for Agent-Based Simulation and Modeling in Transportation Applications a Foreword Agent-based modeling and simulation (ABMS) methods have been applied in a spectrum of research domains. This primer focuses on ABMS in the transportation interdisciplinary domain, describes the basic concepts of ABMS and the recent progress of ABMS in transportation areas, and elaborates on the scope and key characteristics of past agent-based transportation models, based on research results that have been reported in the literature. Specifically, the objectives of this primer are to explain the basic concept of ABMS and various ABMS methodologies scoped in the literature, review ABMS applications emerging in transportation studies in the last few decades, describe the general ABMS modeling frameworks and commonly shared procedures exhibited in a variety of transportation applications, outline the strength and limitation of ABMS in various transportation applications, and demonstrate that ABMS exhibits certain comparable modeling outcomes compared to classical approaches through a traveler’s route choice decisionmaking process example. The target audiences of this primer are researchers and practitioners in the interdisciplinary fields of transportation, who are specialized or interested in social science models, behavioral models, activity- based travel demand models, lane use models, route choice models, human factors, and artificial intelligence with applications in transportation. Monique R. Evans Debra S. Elston Director, Office of Safety Director, Office of Corporate Research, Research and Development Technology, and Innovation Management Notice This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S.
    [Show full text]
  • Coupling Matsim and Urbansim: Software Design Issues
    Working Paper Coupling MATSim and UrbanSim: Software design issues Thomas W. Nicolai, Kai Nagel TU Berlin, Germany Revision: 1 FP7-244557 20/12/2010 Contents 1 Introduction.........................................................................................................................3 2 Introducing new methods and concepts to integrate UrbanSim with MATSim...................5 File-based coupling via data binding........................................................................................ 6 2.1 6 Object-based coupling ............................................................................................................. 8 2.2 8 Java Native Interface (JNI) ............................................................................................ 9 2.2.1 9 2.2.2 JPype ................................................................................................................... 10 2.2.3 Other object-based integration methods.............................................................. 13 3 Discussion ........................................................................................................................15 4 Conclusion........................................................................................................................17 5 References .......................................................................................................................18 i Coupling MATSim and UrbanSim __________________________________________________________ 20/12/2010 Coupling MATSim and
    [Show full text]
  • Simulating the Connected Metropolis Fletcher Foti University of California, Berkeley (USA)
    Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings Volume 14 Portland, Oregon, USA Article 6 2014 UrbanSim2: Simulating the Connected Metropolis Fletcher Foti University of California, Berkeley (USA) Paul Waddell Follow this and additional works at: https://scholarworks.umass.edu/foss4g Part of the Geography Commons Recommended Citation Foti, Fletcher and Waddell, Paul (2014) "UrbanSim2: Simulating the Connected Metropolis," Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings: Vol. 14 , Article 6. DOI: https://doi.org/10.7275/R5JQ0Z61 Available at: https://scholarworks.umass.edu/foss4g/vol14/iss1/6 This Paper is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings by an authorized editor of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. UrbanSim2: Simulating the Connected Metropolis UrbanSim2: Simulating the Connected Metropolis by Fletcher Foti and Paul Waddell in a metropolitan region in order to predict demand for public infrastructure such as transportation, en- University of California, Berkeley (USA). fscot- ergy and water. It has been most widely used for re- [email protected] gional transportation planning, to assess the impacts of transit and roadway projects on patterns of urban Abstract development, and the indirect effects these have on UrbanSim is an open source software platform for travel demand. In recent years, urban models are in- agent-based geospatial simulation, focusing on the creasingly used to understand how to reach sustain- spatial dynamics of urban development. Since its ability goals, including reducing resource use and creation UrbanSim has been used in the official plan- land consumption, and how best to substitute sus- ning processes for at least a dozen regional govern- tainable modes like transit, walking, and biking for ments which were used to help allocate billions of increasing automobile use.
    [Show full text]
  • An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment∗
    An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment∗ Paul Waddell1, Geoff Boeing1, Max Gardner2, and Emily Porter2 1Department of City and Regional Planning, University of California, Berkeley 2Department of Civil and Environmental Engineering, University of California, Berkeley January 2018 arXiv:1802.09335v1 [cs.CY] 8 Feb 2018 ∗Technical report for U.S. Department of Energy SMART Mobility Urban Science Pillar: Coupling Land Use Models and Network Flow Models Abstract Integrating land use, travel demand, and traffic models represents a gold stan- dard for regional planning, but is rarely achieved in a meaningful way, especially at the scale of disaggregate data. In this report, we present a new pipeline ar- chitecture for integrated modeling of urban land use, travel demand, and traffic assignment. Our land use model, UrbanSim, is an open-source microsimulation platform used by metropolitan planning organizations worldwide for modeling the growth and development of cities over long (∼30 year) time horizons. Ur- banSim is particularly powerful as a scenario analysis tool, enabling planners to compare and contrast the impacts of different policy decisions on long term land use forecasts in a statistically rigorous way. Our travel demand model, Ac- tivitySim, is an agent-based modeling platform that produces synthetic origin{ destination travel demand data. Finally, we use a static user equilibrium traffic assignment model based on the Frank-Wolfe algorithm to assign vehicles to specific network paths to make trips between origins and destinations. This traffic assignment model runs in a high-performance computing environment. The resulting congested travel time data can then be fed back into UrbanSim and ActivitySim for the next model run.
    [Show full text]