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 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 for 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-Denison, and Tyler.
Improving Travel Projections for Public Transportation
1995
52 pages
Report
Keine Angabe
Englisch
Transportation & Traffic Planning , Transportation , Road Transportation , Public transportation , Transportation planning , Trip distribution models , Computerized travel forecasting , Traffic estimates , Trip forecasting , Trip frequencies , Estimating , Transportation models , Texas , Traffic generation
Intelligent public transportation system for green travel
Europäisches Patentamt | 2023
|Travel Experience on Travel Satisfaction and Loyalty of BRT Public Transportation
DOAJ | 2019
|Transportation Projections: 1970-1980
NTIS | 1973
|Transportation and Travel: Travel Management
NTIS | 1993