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85 Directions for Coordinated Improvement of Travel Surveys and Models Eric Petersen, RAND Europe Peter Vovsha, PB Consult, Parsons Brinckerhoff Inc. Anumber of recent studies have pointed out the gapbetween academic interest in activity- based modelsand the relative scarcity of activity- based models implemented for regional and statewide planning agencies. The issues that hinder the adoption of activity- based mod- els range from the difficulty in obtaining both resources to reestimate existing models and staff to run more compli- cated models to theoretical concerns over the variability involved in microsimulation. This paper focuses on the data requirements to support the estimation of an activity- based model and will present the minimum requirements and the desirable features to be included in future household sur- veys. The underlying message of this paper should reassure planning directors that the basic surveys required to build an activity- based modeling application are similar to those required to update and revalidate a conventional model, although certain extensions are desirable. A focus on more limited improvements to conventional surveys does not rep- resent a digression from a move toward activity- based models but rather offers a useful intermediate stop on the way and takes practical advantage of what can be already done today or in near future. For modelers wishing to explore the cutting edge of activity- based modeling, the paper also examines two promising areas of research: atti- tudinal and stated- preference (SP) extensions to conven- tional surveys. The paper concludes with a survey of existing household surveys from large metropolitan regions in North America and Europe and examines their suitabil- ity for supporting activity- based models. For a long time, the structure of travel surveys was limited by the considerations of supporting the develop- ment of conventional four- step models. One of the major deficiencies of such models was the matrix structure of the trip distribution and modal- split submodels that severely limited the model segmentation and the number of explanatory variables that could be used. The surveys were actually much richer than the models, and it was not clear why travel surveys should be made even more complicated (and more expensive to collect). Shifting to the microsimulation modeling paradigm has lifted this technical limitation from model segmentation, allowing for richer, more- complex models, and, in turn, fueling the desire for better data. There are several directions in which travel demand models and corresponding surveys can be significantly improved: 1. Widening the range of explanatory variables used in models and collected in surveys, 2. Improving the understanding and modeling of causal linkages across various dimensions of travel behavior, and 3. Adding attitudinal and SP extensions to conven- tional revealed- preference (RP) surveys. Each of these points is described below in detail. These three directions are not independent and actually are closely intertwined. Furthermore, model improve- ment can proceed in incremental steps rather than requiring dramatic improvements in all three areas simultaneously. In a resource- constrained environment, the most practical approach may be to conduct a survey for a convention model, but the authors strongly recom- mend that the standard surveys be enhanced with some
