BEHAVIORAL DEMAND MODELING AND VALUATION OF TRAVEL TIME. ATTITUDINAL DATA

The role of attitudinal data in urban transportation planning was reviewed in this workshop report. The goal of the workshop was to propose stages of research in the investigation and development of a forecasting methodology that associates observed travel behavior with the attitudes of the population toward system attributes and policy variables. The attitudinal models had to satisfactorily relate to the real world and provide a design-directing process in contrast to the present methodology that evolved as a resource-allocation process. It was considered that a valid model of the decision process must (a) include the variables on which people base their decisions, (b) possibly combine sets of these variables into more basic dimensions (multivariate techniques), and (c) describe how people actually use the dimensions or variables to make travel decisions. To implement research results, an evolutionary process of behavioral model development was recommended. This strategy would require improving the modal-choice methodology. This could be accomplished by a modal-choice model which derives choice patterns on the basis of behavioral measures rather than, or in addition to, physical dimensions. This model would provide a true abstract representation of travel modes to facilitate predictions of demand for new as well as existing modes. By directly or indirectly incorporating appropriate measures such as comfort, convenience, and reliability into the prediction algorithm, a significant increase in the explanation of variance over existing models would result.