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An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment


  • Waddell, Paul
  • Boeing, Geoff

    (Northeastern University)

  • Gardner, Max
  • Porter, Emily


Integrating land use, travel demand, and traffic models represents a gold standard 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 architecture 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. UrbanSim 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, ActivitySim, 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. This technical report introduces this research area, describes this project's achievements so far in developing this integrated pipeline, and presents an upcoming research agenda.

Suggested Citation

  • Waddell, Paul & Boeing, Geoff & Gardner, Max & Porter, Emily, 2018. "An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment," SocArXiv 74zaw, Center for Open Science.
  • Handle: RePEc:osf:socarx:74zaw
    DOI: 10.31219/

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    References listed on IDEAS

    1. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    2. Paul Waddell, 2011. "Integrated Land Use and Transportation Planning and Modelling: Addressing Challenges in Research and Practice," Transport Reviews, Taylor & Francis Journals, vol. 31(2), pages 209-229.
    3. Dong, Xiaojing & Ben-Akiva, Moshe E. & Bowman, John L. & Walker, Joan L., 2006. "Moving from trip-based to activity-based measures of accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(2), pages 163-180, February.
    4. Boeing, Geoff, 2017. "Methods and Measures for Analyzing Complex Street Networks and Urban Form," SocArXiv 93h82, Center for Open Science.
    5. Sevcíková, Hana & Raftery, Adrian E. & Waddell, Paul A., 2011. "Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 540-553, July.
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    7. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
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