Earticle

Background/Objectives: This study was conducted to review and verify the effectiveness of the increase in express trains and train volume, which are currently being introduced step by step, through big data analysis, and to suggest additional new alternatives. Methods/Statistical analysis: Therefore, this study used papers and various statistical data to improve congestion on Seoul Subway Line 9 for service diagnosis and evaluation of the current Seoul Subway Line 9, and derived results through R, an open source. Findings: As a result of the analysis, direct trains connecting Gayang and Dangsan, residential areas, to Yeouido and Sinnonhyeon, business-intensive areas, are operated to minimize commuting congestion. Improvements/Applications: The results of this study are expected to be used as useful guidelines for planning not only subway lines 9 but also other subway lines.

Background/Objectives: In this study, through big data analysis, the current situation and cause are identified and a plan to reduce accidents in bicycle accidents is derived. Methods/Statistical analysis: In order to secure data on bicycle traffic accidents, data from Gyeonggi-do were collected and analyzed using R and Tableau, which are big data analysis tools. After collecting the data, it was preprocessed according to the analysis. Findings: As a result of the analysis, it was found that bicycle accidents increased as the bicycle population increased. Therefore, in this study, an intersection notification and a bicycle cross-section were proposed. Improvements/Applications: The results of this study are expected to be used to develop policies that can be prevented in advance while instilling awareness of bicycle accidents.