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Trafficking is a growing problem in cities around the world. Congestions occurring at peak hours have become common problems that all the major cities of the world are facing. Some metropolises, however, have found solutions to reduce traffic jams, especially in peak hours. Problem solutions are given by road traffic management by reducing waiting times and queues, in the same way as traffic safety increases. The first step in achieving coherent management is to achieve a method of collecting traffic data. Under the current infrastructure development conditions, one of the few solutions is given by virtual inductive loops. Inductive loop detectors have become the most utilized sensors in traffic management systems. The gathered traffic data is used to improve traffic efficiency (i.e., warning users about congested areas or planning new infrastructures). This paper aims to develop virtual intersection models by using primary data from virtual inductive loop video analyzers.