Artificial intelligence (AI) has been applied to most industries by enhancing automation and contributing greatly to efficient processes and high-quality production. This research analyzes the applications of AI-based automobile accident prevention systems. It deals with AI-based collision prevention systems that learn information from various sensors attached to cars and AI-based accident detection systems that automatically report accidents to the control center in the event of a collision. Based on the literature review, technological and institutional changes are taking place at the national levels, which recognize the effectiveness of the systems. In addition, start-ups at home and abroad as well as major car manufacturers are in the process of commercializing auto parts equipped with AI-based collision prevention technology.

The present study aimed to compare and analyze the particulars of and difference in medical expenses and their composition ratio for 2,026 patients hospitalized at 2 types of medical institutions (443 at a clinic and 1,583 at a hospital) in Jeonju-si, Jeollabuk-do under coverage of automobile insurance during 2009. From the analysis, it became evident that there were differences in individual characters of inpatients covered by automobile insurance, and details, composition and composition ratio of medical treatment for them depending on types of medical institutions. There was no difference, however, between the total and average medical expenses per capita even when markup rate was applied to the automobile insurance by types of hospitals. The ratio of radiotherapy and physical therapy in the composition of medical expenses was found to be extraordinarily high in clinics compared to that of hospitals. The composition ratio of the fixed cost including charge for hospitalization also turned out to be fairly high in all medical institutions.