Incorporating activity duration and scheduling utility into equilibrium-based Dynamic Traffic Assignment

This paper deals with the problem of jointly modelling activity scheduling and duration within a Dynamic Traffic Assignment (DTA) problem framework. Although the last decades witnessed an intense effort in developing utility-based departure time choice models, relatively little has been done for understanding how the different assumptions on the utility model affect the model outputs. This problem is the main focus of this paper, which evaluates the effect of explicitly incorporating activity scheduling and duration within a generic user equilibrium DTA formulation. While using utility functions to model the positive component of the utility is a quite common procedure, the object of this paper is to show that a generic utility-based framework behaves as trip-based, activity-based, tour-based, or schedule-based if specific assumptions are specified. By establishing a set of properties, we quantify the amount of utility lost due to traffic congestion and how this affects activity (re-)scheduling and duration decisions. This allows predicting the effect of using a different assumption on the evolution of the transport system – and more specifically the departure time choice model. Conclusions support the idea that, under specific conditions, complex user behaviour can be approximated through a simplified model, and that the ratio between utility at origin and destination can be used to identify systematic biases within an existing DTA model – such as anticipating the rush hour. We also propose a novel utility function suited for modelling different activities, which can be used for modelling activities with a different duration. The mathematical model used to evaluate the effect of scheduling and duration into the equilibrium-based Dynamic Traffic Assignment is a simple bottleneck model. While this model has been recently re-formulated in order to capture the interaction between morning/evening commute, this paper further generalizes it in order to account for all type of activities.