A new Advanced Traveler Advisory Tool based on personal user preferences

This paper focuses on an Advanced Traveler Advisory Tool (ATAT) aiming at supporting users travelling on multimodal networks and at suggesting the best path set according to user personal preferences. In order to find the best personal paths, the presented ATAT uses the Random Utility Theory framework to assign an estimation of the path utility perceived by the user for each path alternative. The first part of this paper illustrates the user needs and the ATAT logical architecture, and presents the modeling framework able to provide personalized pre-trip and en-route information. The second part reports the results of some test applications and the results of a benefit assessment of the ATAT use for transit travelers