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Travel demand modeling for the small and medium sized MPOs in Illinois.

File Language:
English


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  • Abstract:
    Travel demand modeling is an important tool in the transportation planning community. It helps forecast travel

    characteristics into the future at various planning levels such as state, region and corridor. Using travel demand

    modeling to evaluate different situations (changes in land use and/or transportation network) would allow

    Metropolitan Planning Organizations’ (MPOs) staff make educated decisions regarding growth and

    improvements to their respective regional transportation networks. Several small (50,000< population

    <200,000) and medium (200,000
    different transportation planning purposes, most commonly, the Long Range Transportation Plan (LRTP) and

    Transportation Improvement Program (TIP). Some of the small and medium sized MPOs in the state of Illinois

    are unable to utilize TDM tools primarily due to lack of available resources and guidelines at the regional and

    state level. This study sought to establish the framework necessary for the development, maintenance, and

    application of small and medium sized MPOs’ TDMs. It is crucial for the local, regional, and state agencies to

    play a collaborative role in the transportation planning process. This study established a framework for

    developing travel demand models at the MPO regional level considering their limited available resources.

    Special attention was given to simplicity and accuracy of the travel model development process. Extensive

    calibration and validation checks were recommended, as accuracy of travel forecasting is of high importance.

    As an important part of this study, a statewide group, the Illinois Modeling Users Group (IL-MUG) was created

    to support, set standards and guide the development, implementation, and maintenance of travel demand

    models in small and medium sized MPOs in Illinois.

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    PDF
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  • Main Document Checksum:
    urn:sha256:36978c07cd755e82c74879883fcab59041b7ae7991199a0516a8ded004f768a1
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  • File Type:
    Filetype[PDF - 1.13 MB ]
File Language:
English
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