Details:

Creators:
Perkinson, Dennis G. ; Keitgen, Brigitta
Perkinson, Dennis G. ; Keitgen, Brigitta Less -
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
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:
PDF
Collection(s):
US Transportation Collection
Main Document Checksum:
[+]
urn:sha256:45b74a8d233a0c19d95677e96e5992b302b8789be285ccc94aeff2ba2a5f26b6
Download URL:
https://rosap.ntl.bts.gov/view/dot/13318/dot_13318_DS1.pdf
File Type:

Supporting Files

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