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Fuzzy logic has been recognised in the literature as an effective methodology for real-time signal control. The majority of the fuzzy controllers in the literature depend on simple logic which in turn depends on the raw data of a single detector. Their input variables are usually simple estimates of traffic measures such as flow, speed or occupancy, estimated from such single-detector readings. A room for improvement is sought in this article by developing a fuzzy logic model (FLM) that could be integrated with smarter 'processing' tools to estimate several traffic measures from multiple detectors on each approach. The estimates obtained from this processing tool are integrated as input knowledge into the FLM. The mathematical formulation of these traffic measures is presented. The fuzzy logic structure is addressed in detail. A simulation model is devised to test the effectiveness of the FLM. The results are presented and discussed in depth. [ABSTRACT FROM AUTHOR]