Selection and Evaluation of Travel Demand Management Measures

Author:

Taylor Christopher J.1,Nozick Linda K.2,Meyburg Arnim H.2

Affiliation:

1. LS Transit Systems, Inc., Bloomfield, N.J. 07003-3069

2. School of Civil and Environmental Engineering, Cornell University, Hollister Hall, Ithaca, N.Y. 14853

Abstract

Travel demand management (TDM) measures are designed to alter the attractiveness of competing travel modes to prompt individuals to carpool or use transit instead of driving alone. Determining the best set of measures for a given area and estimating the effectiveness of the selected measures involve understanding the characteristics of the available transportation modes and of the area's travelers. The process of developing the best, comprehensive set of TDM measures for the Syracuse, New York, area and predicting the effect of those measures are described. Based on a case study of the best TDM measures and their effect in Syracuse, a procedure is presented that can be used for similar studies elsewhere. An effort is made to use data that would be available for similar studies. The evaluation tool is one that would be available in any other area. The main source of information about the travel patterns was census journey-to-work information. Additional information about employment, transit service, roadway congestion, and so forth was derived from planning reports developed by the local metropolitan planning organization. Similar reports should be available in other areas because of the strict planning provisions of the Intermodal Surface Transportation Efficiency Act of 1991. The major conclusion was that it is indeed possible to select an appropriate set of TDM measures for a given study area while relying on only limited, readily available data and tools.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference9 articles.

1. ParkH. C. Traffic Demand Management: Some Possible Techniques for Bangkok. M.S. thesis. Asian Institute of Technology, 1989.

2. Peak-period traffic congestion: A state-of-the-art analysis and evaluation of effective solutions

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