A doubly dynamic assignment model for the simulation of Advanced Travelers Information Systems

The increasing development of telematics technologies has given rise in the last decades to many interesting applications to the field of transportation. An example is given by the Advanced Travelers Information Systems (ATIS), i.e. innovative technologies aiming at providing travelers with information on network performances in the attempt to facilitate their travel choices. Most of these technologies are conceived to give guidance on en-route travel choices such as route and parking choices, although more recent applications show that the impacts of such systems can also affect other pre-trip choice dimensions such as departure time, trip destination and so on. According to the temporal nature, we can distinguish the information in three categories (Ben Akiva et al., 1991):  historical information, based on the state of the network in the past (e.g. during the previous day);  real-time information, based on the current state of the network and  predictive information, based on the forecasting of the (future) network conditions, which the drivers actually will encounter when travelling within the system .