Improving Travel Projections for Public Transportation
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Improving Travel Projections for Public Transportation

Filetype[PDF-2.46 MB]


  • English

  • Details:

    • Corporate Contributors:
    • Resource Type:
    • Geographical Coverage:
    • 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.

    • Format:
    • Main Document Checksum:
    • File Type:

    Supporting Files

    • No Additional Files

    More +

    You May Also Like

    Checkout today's featured content at rosap.ntl.bts.gov

    Version 3.21