A user equilibrium model for combined activity-travel choice under prospect theoretical mechanisms of decision-making under uncertainty

Rather than considering single trips as the unit of analysis, the activity-based modeling paradigm of travel demand analysis has led to reconceptualizations and innovations in traffic flow models by focusing on complete daily activity-travel patterns. The vast majority of these travel demand and traffic flow models have either implicitly or explicitly assumed that travelers choose between alternatives by maximizing their utility under a deterministic representation of the choice alternatives. While this behavioral assumption leads to tractable, easy-to-apply models, the validity of the assumption largely went untested. This paper investigates the user equilibrium of activity-travel patterns under uncertainty from the perspective of prospect theory. A formulation of the static activity-based user equilibrium model is proposed. In particular, we adopt the concept of a multi-state supernetwork to represent the choice space of activity-travel patterns. A numerical example using hypothetical scenarios is presented to illustrate the proposed model and solution algorithm.