A Mathematical Model for Evaluation of Information Effects in ATIS (Advanced Traveler Information Systems) Environment

Abstract

Travel choices are made according to people's personal preferences and knowledge of the system. Since increase, improvement and updating of knowledge is achieved through information, consequentially information itself is a crucial issue in transportation problems. If information was perfect, users could easily choose the best path from their point of view. but unfortunately complete and precise information about network conditions is rarely available, therefore uncertainty can cause anxiety and stress in decision makers. In specific technical literature, uncertainty has been usually modelled through random utility models. Randomness is then used to represent uncertainty, and therefore the probability of a choice can be calculated. Since recent studies linked uncertainty to the concepts of approximate reasoning rather than randomness, in this paper we quantify the influence of information provision on drivers' behaviour, according to Uncertainty-based Information Theory. A modelling framework based on Evidence Theory, measuring the Belief rather than the Probability of a choice, has been carried out to represent the uncertainties in the perception of travel attributes. A sequential model has been also used to simulate updating of user knowledge, and finally a numerical application shows that users' trust level in information plays a relevant role in choice processes. Within this framework, the importance of conditional Uncertainty in updating knowledge of the system results evident.