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Title:SACSIM: An applied activity-based model system with fine-level spatial and temporal resolution PDF Logo
Authors:Bradley, Mark
Bowman, John L.
Griesenbeck, Bruce
Issue Date:2010
Citation:[Journal:] Journal of Choice Modelling [ISSN:] 1755-5345 [Volume:] 3 [Year:] 2010 [Issue:] 1 [Pages:] 5-31
Abstract:This paper presents the regional travel forecasting model system (SACSIM) being used by the Sacramento (California) Area Council of Governments (SACOG). Within SACSIM an integrated activity-based disaggregate econometric model (DaySim) simulates each resident's full-day activity and travel schedule. Sensitivity to neighborhood scale is enhanced through disaggregation of the modeled outcomes in three key dimensions: purpose, time, and space. Each activity episode is associated with one of seven specific purposes, and with a particular parcel location at which it occurs. The beginning and ending times of all activity and travel episodes are identified within a specific 30-minute time period. Within SACSIM, DaySim equilibrates iteratively with traditional traffic assignment models. SACSIM was calibrated and tested for a base year of 2000 and for forecasts to the years 2005 and 2035, and was subjected to a formal peer-review. It was used to provide forecasts for the Regional Transportation Plan (RTP) and continues to be used for various policy analyses. The paper explains the model system structure and components, the integration with the traffic assignment model, calibration and validation, sensitivity tests, model application and Federal peer review results. We conclude that it is possible to create and apply a regional demand model system using parcel-level geography and half-hour time of day periods. Experiences thus far have pointed to major benefits of using detailed land use variables and urban design variables, but also to new challenges in providing parcel-level land use inputs for future years
Subjects:travel demand forecasting
activity-based models
microsimulation
Creative Commons License:http://creativecommons.org/licenses/by-nc/2.0/uk/
Document Type:Article
Appears in Collections:Journal of Choice Modelling

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