Abstract Technology forecasting is about understanding a status of a specific technology in the future, based on the cur-rent data of the technology. It is useful when planning technology management strategies. These days, it is com-mon for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts’ opinions. However, this qualitative method of technology foreca sting is costly and time consuming since it re-quires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of t echnology forecasting based on quantitative analysis. The methodology consists of data collection, principa l component analysis, and technology forecasting by logistic regression, which is one of the data mining techniq ues. In this research, patent documents related toautonomous vehicle are collected. Then, the texts from patent d ocuments are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performedby using principal component score. On the basis of this result , it is possible to analyze R&D development sit-uation and technology forecasting. Key Words : Technology Forecasting, Patent, Logistic Regression, Autonoum ous vehicle, Principal component analysisReceived: Sep. 14, 2014Revised : Sep. 28, 2014Accepted: Jan. 20, 2015
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