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Selecting optimal routes to reduce travel time has been an important research area for urban traffic network managements. Various parameters such as route length, average speed and event situations need to be considered in the design of a route guidance system. In this paper, we develop a new navigation system based on the combination of fastest path search algorithm and travel time prediction method for urban traffic areas. Compared with previous route guidance systems, the results reveal that our system, applying the prediction based realtime fastest path (PRFP) algorithm, can significantly reduce the travel time especially when customers travel in a complex route environment and face frequent congestion. We also demonstrate the advantages of this system and verify the results using simulation.