A fuzzy decision support system for traffic control centers

Abstract

We present a fuzzy decision support system that can be used in traffic control centers to provide a limited list of appropriate combinations of traffic control measures for a given traffic situation. The system is part of a larger traffic decision support system (TDSS) that can assist the operators of traffic control centers when they have to reduce non-recurrent congestion using a network-wide approach. The kernel of the system is a fuzzy case base that is constructed using simulated scenarios. By using the case base and fuzzy interpolation the decision support system generates a ranked list of combinations of traffic control measures. The best combinations can then be examined in more detail by other modules of the TDSS that evaluate or predict their performance using macroscopic or microscopic traffic simulation. At a later stage the fuzzy decision system will be complemented with an adaptive learning feature and with a set of fuzzy rules that incorporate heuristic knowledge of experienced traffic operators.