Intelligent isolated intersection

In this research, an "intelligent" isolated intersection control system is developed. This paper proposes a two-step process that develops the rules of fuzzy control. In the first step, the best sequence of phases is developed for many different patterns of vehicle arrivals. These sequences are developed using a genetic algorithm approach. In the second step, learning from the best strategies, specific rules are defined. The uniqueness of the proposed approach is that the rules are derived from the set of chosen examples assuming that the future traffic arrival patterns are known. This approach also allows a better evaluation of the performance of the fuzzy control because the best solution developed in the first step is used as the reference. The results were found to be very close to the best solution assuming that the future arrival pattern is known