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Mining the GPS big data to optimize the taxi dispatching management

Nowadays the GPS (Global Positioning System) is a common technology where adopted in the transportation system including taxi. Even though the convenient mass transportation such as subway and buses already existing; many people in the Seoul city, Republic of Korea also use a taxi as transportation mode in their daily activity. The problem still existing where many taxi's driver are driving without the passenger, many of the driver only using their intuition and experience to get the passenger. By mining the taxi raw GPS big data, this paper proposes the basic information of taxi passenger distribution in Seoul city. The data is analyzed using multidimensional analyzed where the parameter location, time and frequency are mainly used. The general taxi passenger distribution result shows that Gangnam district got the highest number of passenger; especially from Teheran street. From the specific area, Dongdaemun market also give the high contribution of taxi passenger where around 25% are used taxi when many people went out to shopping. The riding time analysis result shows that 30 % of passengers are rode the taxi in short time and use inside their district only; not across to the others district. Using this basic information, the taxi company can consider and manage their taxi dispatching location to increase the company service and profit.