Aggregate Rail Ridership Forecast (ARRF Sample Clauses

Aggregate Rail Ridership Forecast (ARRF. The Aggregate Rail Ridership Forecast (ARRF I), is a sketch planning tool developed by AECOM and sponsored by FTA. It uses CTPP 2000 data and GIS information to develop an estimate of ridership potential for a new rail system. The model is based on data for twenty recently built light rails and commuter rails. Two different sets of models were developed, respectively for LRT (light rail) and CR (commuter rail). The models were simple regression formulas based on journey-to- work (JTW) flow data occurring within specific distance buffers of rail stations cross tabulated by socioeconomic and workers’ density. In particular, the LRT model used CTTP flows by employment density. The CR model used CTTP flows stratified by employment density and income as well as level of service variables such as speed, train miles per direction route, and connection to rail distributor. The final dependent variable is the weekday unlinked trips. Models were calibrated based on available data from the National Transit Database for the period of 2000-2002. Eleven cities were used for the LRT model, including Baltimore, Buffalo, Cleveland, Dallas, Denver, Portland, Sacramento, Salt Lake City, San Diego, San Xxxx, and St. Xxxxx. Nine different commuter rail systems were used to calibrate the CR model, including Baltimore-DC MARC, Dallas-Ft. Worth TRE, LA Metrolink, Miami Tri-Rail, San Diego Coaster, San Francisco Caltrain, San Xxxx ACE, Seattle Sounder, Washington DC VRE. An enhanced version of the model, ARRF II, was further developed. Some of the modifications included one unified CR/LRT model, more accurate characterization of trips, and improved CTPP data processing, etc. Separate models were estimated for four different purposes, including home-based work with walk access, home-based work with drive access, others with walk access, and others with drive access.
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