In modern societies the demand for mobility is increasing daily. Hence, one challenge to researchers dealing with traffic and transportation is to find efficient ways to model and predict traffic flow, even if the behaviour of people in traffic is not a trivial problem. Increasingly more people travel longer distances and choose more complex routes and transportation means. Thus, the social nature of traffic (e.g. coordinated decisions) seems to be a key question, not well explored. There are already systems designed to help drivers to make traffic decisions (broadcast, internet, etc.). However, such systems cannot process any feedback from the users. We aim at creating a model of drivers as social agents, thus allowing their behaviour to be predicted and considered in the simulation. This may, on its turn, improve the accuracy of the existing Advanced Travel Information Systems (ATIS).
Ana L. C. Bazzan, Joachim Wahle, Franziska Klü