Improving Travel Projections for Public Transportation

Details

• Creators:
  Perkinson, Dennis G. ; Keitgen, Brigitta
• Corporate Contributors:
  Texas A & M University
• Subject/TRT Terms:
  Forecasting Peak Periods Ridership Trip Generation
• DOI:
  https://doi.org/10.21949/1404652
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas ; United States
• Corporate Publisher:
  Texas Transportation Institute. Texas A&M University
• 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 the 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 from 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.
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:03d15c6014763c80bf4dac10014c38325e35daa60fc266c5bd51a787e430ddc7517c09353efd5cca492d92b4069a404f570b98720f2c77bff9f9d6b4dc509b59
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/13318/dot_13318_DS1.pdf
• File Type:
  [PDF - 2.46 MB ]