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Comparison of models of individual choice in a complex setting

In response to gasoline shortages, pollution problems and the rise in oil prices, it is clear that individual commuting habits may be modified. To assist planners in evaluating the impact of alternative policies, models of individual behavior in complex mode choice environments are necessary. This paper examines the use of simulation in association with statistical methodologies to verify models of traveler behavior. The data employed in the calibration and evaluation of the models was derived in a large scale longitudinal study. In conjunction with an UMTA demonstration project, policy makers were able to manipulate the cost and service of the transportation alternatives and observe in detail the responses over time of a large sample of individual users for whom extensive amounts of socio-economic data had been collected.