Usage of fuzzy logic based data mining methods in analysis of public transportation data

Intelligent Transportation Systems are used to construct and manage public transportation system based on knowledge efficiently and also to increase interest of people for public transport. In scope of this thesis, subtopics of these systems, Advanced Public Transportation Systems and Advanced Traveler Information Systems have been addressed respectively, and two separate applications have been developed. In this study, by examining boarding data obtained from smart cards used in public transportation system in Izmir, estimation of alighting stop for bus mode has been firstly dwelled on. A solution related to these situations, are rarely encountered in literature, about boarding once a day and multiple boarding with same card on same service has been proposed. Moreover comfort degree of passenger in bus has also been estimated by using detailed boarding-alighting information related to requested day, line and its service. In this study, solution has been sought to multi-criteria fuzzy route planning problem as an application of Advanced Traveler Information Systems. For the first time in the literature, fuzzy neighborhood relations between stop-stop, line-stop and line-line, and fuzzy preference degree of stop have been discussed. Information obtained by alighting estimation method has been utilized while stop activity which is one of criteria constituting the fuzzy preference degree of stop has been calculated. It will be possible to develop route planner system similar with human-reasoning thanks to fuzzy concepts used in route planning problem. It is thought that this study will provide contribution to researchers and recently popular issues; smart cities and sustainable mobility.