acknowledges substitution and complements effects that might exist between various modes.

The constant elasticity of demand approach proposed requires basic information on the cost and time components of modal trips, on the initial mode share. By entering the impact on the generalized cost of travel of a given policy or program, the model estimates the impact on the final mode shares. These data requirements are described in greater detail in the next section of this report.

The model estimates impacts on travel behavior in a synergistic fashion. That is, the model allows the simultaneous impact assessment of several TDM policies or strategies, where the final total impacts are greater than the sum of the impact of each individual strategy. In addition, the constant elasticity of demand equation (5) assures that impacts are assessed in a multiplicative, rather than an additive, fashion avoiding impacts overestimation. For example, if one strategy (e.g., a transit subsidy) reduces SOV use by 5 percent and another strategy, say parking pricing, reduces SOV use by an additional 7 percent, the total combined effect is a 11.5 percent reduction( calculated as 100% - [95% x 93%]), rather than a 12 percent reduction (linearly calculated as 7% + 5%).

Another advantage of the model is that it allows program evaluation based on incremental impacts. For example, under the constant elasticity demand framework the congestion reduction benefits of a shift from SOV to transit is the difference in congestion impacts between SOV and transit travel. Using a base case approach (a

scenario where a policy or benefits of shifting from distinguishing between peak

program is not implemented), SOV to alternative modes. and off-peak impact estimation

the model estimates the net Also, the model permits at an urban area level.

One of the constraints related to the use of elasticities relates to timeframes employed when empirically estimating their values. Applied work generally employs short and medium terms (3-5 years), thus tending to underestimate the full, long term effects of price and service changes. In other terms, increasing (reducing) a transit fare has more negative (positive) effects than what generally predicted by most models.

# Soft Program Trip Change Adjustments

The preceding model estimates the impact on trip behavior of policies affecting the generalized cost of driving, thus allowing the impact of the following TDM strategies to be captured.

The constant elasticity of demand model is best suited for strategies that directly affect the generalized cost of driving, and a set of TDM strategies, such as:

•

Parking pricing;

•

Modal subsidies;

•

Pay as you go schemes;

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