Abstract
This paper presents some theoretical and operative aspects of TVPTA (Tor Vergata Personal Travel Advisor), an Advanced Traveller Advisory Tool (ATAT) under development at the Transport Centre of the “Tor Vergata” University of Rome. It should be able to assist users travelling on multimodal networks, suggesting the best paths according to their personal preferences. Such paths are individuated on the basis of the estimation of a perceived path utility formalised within the Random Utility Theory.The first part of this paper illustrates the user needs, the logical and the functional architecture of TVPTA; it also includes the transit modelling framework to provide personalized pre-trip information and the learning process to capture individual preferences. The second part describes an implementation example of TVPTA concepts in the metropolitan area of Rome (Italy).
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