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Title: MODELING MODE CHOICE IN NEW JERSEY
Accession Number: 00476108
Record Type: Component
Availability: Find a library where document is available Abstract: In this paper, a mode choice model developed for NJ Transit and the Port Authority of New York and New Jersey to assist in the evaluation of proposals for increasing the capacity and use of the existing Hudson River crossing connecting Manhattan and northern New Jersey is described. The model focuses on the choices of a.m. peak period eastbound commuters. It allocates demand across seven primary modes, including automobile, bus, two park-and-ride modes (automobile to bus and automobile to PATH), and three rail modes (commuter rail to Penn Station, commuter rail with transfer to PATH, and local access to PATH). The emerging trans-Hudson crisis that provided the impetus for the model development effort, the planning program of which it was a part, the data sources used in the effort, the specification of the model, the procedures used to estimate the model coefficients, the statistical results of the model estimation, and the model's forecasting performance are also discussed.
Supplemental Notes: Publication of this paper sponsored by Committee on Passenger Travel Demand Forecasting. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
Monograph Title: Monograph Accession #: 01418189
Authors: Neels, KevinMather, JosephPagination: pp 20-27
Publication Date: 1987
Serial: ISBN: 0309046505
Media Type: Print
Features: References
(1)
; Tables
(6)
TRT Terms: Identifier Terms: Uncontrolled Terms: Geographic Terms: Old TRIS Terms: Subject Areas: Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning
Files: TRIS, TRB, ATRI
Created Date: Sep 30 1988 12:00AM
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