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Proposed Prediction Model

In this section, we propose an alternative approach to estimating the impact of TDM strategies. The evaluation framework follows a basic structure for consistent assessment and comparison as found while reviewing relevant guidelines and procedure manuals[11, 12, 18, 19]. The approach embraces the best elements of currently available predictive evaluation methods, while overcoming their constraints identified in the previous section, namely:

  • It uses best derived measures of price sensitivity;

  • It follows a consumer surplus framework;

  • It captures important transportation users’ trade-offs;

  • It can assess short and long run impacts; and,

  • It goes beyond emission control impact evaluation.

Figure 2 outlines the analytical process, which consists of the following steps:

1-

2-

Modeling Technique – This step identifies the theoretical framework to predict how a policy change or program implementation will affect travel behavior. The modeling technique overcomes the constraints linked to the use of coefficients derived from generalized travel demand forecasting models, as described in the previous section. Impact Measures – This step links the change in travel behavior to a set of impact

measures to be used for evaluation. objectives. The objective of this study is

Impacts are determined in terms of to evaluate the impact of TDM in terms

of costs and benefits as viewed by a public transportation agency. Therefore, line with the literature review findings, the impact measures comprise the set costs and benefits as perceived from a societal viewpoint.

in of

3-

Evaluation Metric – evaluation approach

In this final to determine

step, the program

impact measures are used within an effectiveness. The evaluation follows

established guidelines that fall ultimately prices out the value of

within a benefit/cost analysis framework that a single vehicle trip diverted from the network.

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