Information paradoxes in traffic networks

In this paper, we examine the impact of information on the routing decisions that drivers make in a congestible two route traffic network. We present a model and theoretical predictions of driver choices in this network and compare outcomes under conditions of full information and partial information regarding the capacities of each route. In certain circumstances, the model predicts a paradox: aggregate travel delays increase once drivers are a priori informed regarding (stochastic) travel conditions such as adverse weather. We report evidence supporting this paradox in a computerized laboratory experiment in which a large group of subjects repeatedly interact with one another. We analyze both the travel costs associated with each information condition and the individual and aggregate route choices that generate these costs.