Individual Decisions and Collective Effects in a Simulated Traffic System

Abstract

The interdependence of the time-dependent behavior of traffic flows and tripmakers' departure time decisions is central to the analysis of congestion phenomena. The study of the day-to-day dynamics of this interaction in the field is hampered by the inability to obtain adequate data. This paper presents an experimental approach involving real commuters, whereby a traffic simulation model is used to predict congestion patterns under given departure distributions resulting from the actual decisions of the individual participants. These decisions are updated daily, in response to information on prior system performance predicted by the simulation model. The results of this experiment are described in this paper, with emphasis on the system's evolution and dynamic properties, particularly convergence. In addition, concentration and congestion patterns as well as the associated travel time variability are addressed. Initial insights into the processes underlying user behavior in this system are also presented.