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This paper presents a quick-response incremental travel demand forecasting method that uses travel demand elasticities and readily available ground count travel and land use data. Elasticities are defined and criteria for selecting elasticities are identified. The steps for calculating each component of travel affected by a transportation improvement are described. Personnel and computational requirements for this method are greatly reduced relative to those necessary for forecasting with the conventional four-step sequential process (trip generation, distribution, modal split, and trip assignment). The basic travel behavior assumptions of the method are similar to those inherent in conventional models although, in contrast to sequential derivation and application of these models, internally consistent causal relations are maintained. A range of outputs of interest to policymakers is generated, including changes in total travel, changes in mode-specific travel, and changes in travel on a given route or link. The elasticity-based method has recently been used to forecast patronage on the four major transit alternatives included in the Baltimore North Corridor alternatives analysis. This application is described in the paper and compared with forecasts made in a particular application of the conventional four-step sequential travel demand forecasting system for the same alternatives under the same conditions. This direct comparison of the two forecasting methods provides a unique opportunity to assess the effects on forecast patronage of many assumptions inherent in typical applications of each method. (Author)
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