Dynamics of Activity Time-of-Day Choice

This study explored travelers' decision behavior in selecting activity start times. The study examined the problem in the context of the Agent-based Dynamic Activity Planning and Travel Simulation (ADAPTS) activity-based travel demand model for the Chicago, Illinois, metropolitan area. A unique feature of the ADAPTS framework is its consideration of planning horizons for various activity attributes. Naturally, the various attributes of an activity-such as start time, duration, location, party involvement, and mode of travel-can be planned in different time horizons. An attribute that is planned affects the choice of other activity attributes. Therefore, developing a true behavioral time-of-day choice model would not be possible unless the planning order of activity attributes and the dynamics of travelers' decision-making processes are taken into account. Similarly, it can be argued that there should be fundamental differences in the time-of-day decision process when other attributes of the activity are not yet planned but are to be decided at a later time. The presented time-of-day model aims to capture the dynamics of this decision process by considering the planning time horizons of other attributes of the activity, as well as the outcomes of the decisions. The study adopted the discrete choice approach to model activity timing decisions and a hybrid utility maximization and developed a regret minimization model to account for the heterogeneity of decision rules across choice variables. Analysis of the estimation results and parameter elasticities indicates that higher expected travel time, variations in travel time, and schedule occupancy rates for different time choices can significantly increase the regret value of the corresponding choice and therefore affect the time-of-day choice.