Behavioral Foundation of Route Choice and Traffic Assignment Comparison of Principles of User Equilibrium Traffic Assignment Under Different Behavioral Assumptions

Although traffic assignment models are routinely used in transportation operations and planning applications, the behavioral foundations of the models, as well as the practical implications of various behavioral assumptions, are rarely discussed. This paper compares and criticizes the behavioral realism of traffic assignment models. Deterministic, stochastic, boundedly rational, and behavioral user equilibrium principles are studied analytically and numerically on a large real-world network. Behavioral theories underlying these assignment principles range from perfect to bounded rationality, from normative constructs (what decision makers should do) to positive constructs (what decision makers actually do), and from utility-maximizing to rule-based decision-making paradigms. The discussion highlights an emerging positive modeling approach that incorporates empirically derived behavior rules in the analysis of route choice. Results show significant discrepancies between link flow estimates arising from different behavioral foundations. For instance, compared with traffic assignment models with more realistic behavioral assumptions, models assuming perfect or substantive rationality can significantly underestimate the level of congestion on the most congested links (e.g., freeway bottlenecks).