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Improving Travel Projections for Public Transportation

Filetype[PDF-2.46 MB]


English
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Details:

  • Creators:
  • Corporate Contributors:
    Texas A & M University
  • Subject/TRT Terms:
  • DOI:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Texas
  • TRIS Online Accession Number:
    00711361
  • NTL Classification:
    NTL-PUBLIC TRANSPORTATION-PUBLIC TRANSPORTATION
  • Abstract:
    Public transportation use saves energy and reduces emissions by taking people

    out of single passenger automobiles and putting them into high occupancy, energy

    efficient transit vehicles. Furthermore, public transit ridership and vehicular

    trip estimates are the base information required for estimating energy

    consumption and air pollution. Trip generation models as developed and used

    within Texas predict the number of trips expected to occur in a typical 24-hour

    day. The need to estimate peak=period trips has generated innovative techniques

    for estimating peak-period travel from teh 24-hour trip tables. Improved

    methods of estimating the number of trips that will be generated during the peak

    period will potentially improve the estimation of ridership on public

    transportation, as well as related energy and emission forecasts. This project

    produced a trip generation model fro predicting peak-period trips based on the

    travel surveys conducted in Texas during 1990 and 1991 for Amarillo,

    Beaumont-Port Arthur, Brownsville, San Antonio, Sherman-Dension, and Tyler.

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