Emissions Analysis Techniques for TCMs
Overview - The CUTR_AVR model predicts changes in average vehicle ridership (AVR) resulting from employer-based TDM programs.
Strategies Addressed - Carpooling and vanpooling promotion; telecommute and work hour strategies; pricing and subsidies.
Methodology - The CUTR_AVR model uses an artificial neural network to predict mode share and average vehicle ridership based on attributes of the employer-based TDM program. TDM program effects can be analyzed either individually or in combination with each other. The model is based on a dataset including 7,000 employer trip reduction plans from three metropolitan areas in Arizona and California. The model is particularly applicable at the site level for single employers with 100 or more employees or multiple employer sites.
Data Requirements - Data are required on the employment sites to be evaluated, including current mode share, number of employees, and area population.
Outputs - Changes in modal share and average vehicle ridership.
Level of Effort - The CUTR_AVR model is easy-to-use, off-the-shelf software. Minimal effort is required to develop the data inputs.
Advantages - Positive attributes include 1) the model is based on a large, real-world data set; 2) it allows non-linear/non-additive effects of programs; 3) effectiveness can vary by the size of the company; and 4) results from multiple employment sites can be combined. The model performed well in a comparison with other TDM evaluation models. The model is best suited for evaluating impacts of TDM programs that cannot be quantified through time and cost changes.
Limitations - The model evaluates only a subset of specific TDM programs. Different levels of program implementation or participation are not considered - each program is either implemented or not implemented. Similarly, the model is not sensitive to varying levels of financial or time-based incentives. The model does not calculate VMT or emissions reductions.
Source/Availability - The CUTR_AVR model, developed in 1999, is available from the Center for Urban Transportation Research (CUTR) at the University of South Florida. It can be downloaded at no charge from CUTR's National TDM and Telework Clearinghouse; (http://www.cutr.eng.usf.edu/). For information contact Phil Winters (email@example.com).
For additional documentation, see Winters, et al. Predicting Change in Average Vehicle Ridership Based on Employer Trip Reduction Plans. Paper submitted to the 78th Annual Meeting of the Transportation Research Board (Paper no. 990484), January 1999.