In modern motoring, many factors are considered to realize driving convenience and achieving\nsafety at a reasonable cost. A drive towards effective management of traffic and parking space allocation\nin urban centres using intelligent software applications is currently being developed and\ndeployed as GPS enabled service to consumers in automobiles or smartphone applications for\nconvenience, safety and economic benefits. Building a fuzzy logic inference for such applications\nmay have numerous approaches such as algorithms in Pascal or C-languages and of course using\nan effective fuzzy logic toolbox. Referring to a case report based on IrisNet project analysis, in this\npaper Matlab fuzzy logic toolbox is used in developing an inference for managing traffic flow and\nparking allocation with generalized feature that is open for modification. Being that modifications\ncan be done within any or all among the tool�s universe of discourse, increment in the number of\nmembership functions and changing input and output variables etc, the work here is limited\nwithin changes at input and output variables and bases of universe of discourse. The process implications\nis shown as plotted by the toolbox in surface and rule views, implying that the inference\nis flexibly open for modifications to suit area of application within reasonable time frame no matter\nhow complex. The travel time to the parking space being an output variable in the current inference\nis recommended to be substituted with distance to parking space as the former is believed\nto affect driving habits among motorist, whom may require the inference to as well cover other\nimportant locations such as nearest or cheapest gas station, hotels, hospitals etc.
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