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Toward a More Efficient Network Structure for Travel Demand Modeling

File Language:
English


Details

  • Creators:
  • Corporate Creators:
    University of Florida (Gainesville)
  • Corporate Contributors:
  • Subject/TRT Terms:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
  • Edition:
    Final report, January 2018 – December 2019
  • Corporate Publisher:
    Florida. Department of Transportation
  • Abstract:
    The travel demand models in Florida use different road networks even in geographically overlapping areas. Due to differences in network segmentation and details, currently, it is difficult to share information among models at different scales. Thus, this research examines the issues related to the network structure of travel demand models, with an emphasis on the Statewide model. It aims to identify a more efficient multi-scale network structure that will enable effective information sharing between the Statewide models and the district or local models, while preserving the detailed information provided by finer network segmentation. After considering previous research and practice in and out of Florida on this topic, this research proposes a framework for a planning network database to support efficient travel demand modeling for the state of Florida. The proposed planning network database uses a unified true-shape network, which includes all public roads, supports Linear Referencing System (LRS) to access the Florida Department of Transportation's (FDOT’s) Roadway Characteristics Inventory (RCI) data, and supports multi-scale travel demand modeling and eventually, multi-resolution transportation simulation modeling. The network structure supports different scales of models and the ability to store various planning scenarios. Travel-demand modeling projections can be stored in the database which can help planners and decision makers on future planning applications. Therefore, the database provides a unified network for modeling consistency and efficient data sharing at the network level. It supports various transportation data sources, increases the efficiency in preparing a network ready for modeling, and reduces the redundancy workloads among multiple transportation agencies. To ensure successful implementation and the long-term sustainability of the network database, the authors provide some recommendations regarding data sources, modeling software, organizational and database structures.
  • Format:
    PDF
  • Funding:
    BDV31-977-87
  • Collection(s):
  • Main Document Checksum:
    urn:sha256:a77349df479ce3c9b36f376b44216c910bf2b3bebe19d057fa6700ea8ce46b30
  • Download URL:
  • File Type:
    Filetype[PDF - 2.17 MB ]
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