Simulation Studies on Adaptive Route Decision and the Influence of Information on Commuter Scenarios

Abstract

Finding the optimal distribution of vehicles in a traffic network—the one which would minimize the commuting time for every driver—is a challenge traffic engineers have been pursuing for a long time. Various approaches have been proposed which at least seek to come as close as possible to the optimal distribution. Most of these approaches are based on network parameters such as topology, flow of vehicles between given origins and destinations, timing of the traffic lights, etc. Our approach seeks to study the effects of simply giving information to the drivers so that they can be distributed more fairly (from the overall system or network point of view) between two routes. Here we extend our previous work on the influence of information on the decision-making process by drivers. Due to the social nature of traffic, most of these decisions are not independent. On the contrary: the interdependence of actions leads to a high frequency of implicit coordination decisions. Although there are already systems designed to assist drivers (radio, Internet, etc.), these systems do not consider or even have a model of the way drivers decide. Our overall research goal is the study of commuting scenarios, drivers' decision making, and its influence on the system as a whole. The present paper addresses three of these issues: simulation of driver decision making, the role of a traffic forecast component, and a kind of “manipulation” of the traffic state information. The former involves no information being given to drivers, and aims simply at studying an adaptive route decision mechanism, while the goal in the second case is to assess the effect of providing forecast information to the adaptive drivers. The latter issue regards the effect of manipulating information in order to distribute drivers along the network in a way which is close to the system optimum.