A utility-based analysis of activity time allocation decisions underlying segmented daily activity-travel patterns

This paper reports the results of an application of the Aurora model to estimate the utility functions underlying activity-duration decisions in daily activity-travel patterns. Multidimensional sequence alignment is used to derive segments for activity-travel diary data, collected in the Amsterdam-Utrecht corridor in the Netherlands. The profiles of the resulting segments are derived from a descriptive analysis of sociodemographic variables. A tailored genetic algorithm is then used to estimate the parameter of an asymmetrical utility function for each of the resulting segments. The results suggest that the utility of activity duration varies between activities and between segments, and hence sociodemographics.