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