자율주행 트럭 운송산업의 융합기술군 발전 추이 규명을 위한 특허 인용 네트워크 분석

Abstract

Technology convergence among different industries is critical in terms of creating high-value by providing new products or services. Recently, technology convergence between self-driving technology implemented in trucks and different industries is expected to be the driving force of technological innovation, and the importance of the analysis of the convergence technologies between self-driving technology implemented in trucks and different industries is increasing. In this study, we try to identify the main technology convergence between the truck industry and different industries and observe the characteristics of the change in convergence technology. In particular, this study used the forward citation method to overcome the limitation of the concept of Technology Cycle Time (TCT) which does not reflect the influence of technology. Then, community detection was conducted on the series of citation networks of patents formed over TCT period used a moving window size by one year. Next, we calculated the similarity of two consecutive communities over adjacent windows to investigate the overlap of the communities. When we analyzed the most frequently cited self-driving technology patents implemented in the truck industry and the IPC code that cited those patents in the community, we found that the main technology convergence between the truck industry and different industries are the railway power monitoring system, air purification system of fire industry, systems supporting medical activities. The results of this study will provide meaningful information to companies seeking to establish R&D related to the convergence technology of truck industry in which self-driving technology is implemented.