Travel Decision Making Under Uncertainty and Road Traffic Behavior: The Multifold Role of Ambiguity Attitude

Abstract

To aggregate commuters’ mode choices to traffic behavior in the presence of travel time uncertainty, we develop a dynamic traffic simulation in terms of an agent-based model, which consists of two sub-models, the mode choice model and the traffic flow simulation model. The modeling framework accommodates the interplay between the two models and their co-evolution over time. We embed an extended list of empirical parameters including ambiguity/risk attitudes and heterogeneity , and time-money trade-offs within a rank-dependent and source-dependent utility framework to imitate commuters’ daily mode choice behaviors. The improved behavioral realism at the micro-level results in an improved understanding of traffic flow in terms of modal split and average speed at equilibrium, compared to a conventional model which assumes risk neutrality and ambiguity neutrality. A novel finding is that ambiguity seeking, a typical behavior in the loss domain but largely ignored in the transport literature, acts as an important driver that shifts commuters from cars to public transport.