A novel concepts for the study of fuzzy sets similarity and their applications to incident awareness in intelligent transportation systems

The main purpose of this paper is to develop a general analytic framework for studying similarity of fuzzy sets, which provides a new look into information granulation serving as a basis for the incident awareness technique in Intelligent Transportation Systems. To this end, we propose novel concepts and two approaches to fuzzy sets similarity based on the Brouwerian lattices and topology structures. In addition, we consider definitions and differences concerning proposed approaches including relations and operations over fuzzy sets in detail. Then, we impose new definitions for information granulation with proximity and similarity relations. Finally, we apply these concepts at solving an incident awareness problem to illustrate their applicability in Intelligent Transportation Systems.