| Title |
Correlation Analysis between Accident Types and Causes of Railway Vehicles Using R-Studio |
| Authors |
신한철(Shin, Han-chul);김시곤(Kim, Si-gon) |
| DOI |
https://doi.org/10.12652/Ksce.2025.45.3.0413 |
| Keywords |
철도사고 발생 유형, 철도사고 발생 요인, 데이터 전처리, 통계적 유의성 Types of railway accidents, Causes of railway accidents, Data preprocessing, Statistical significance |
| Abstract |
This study systematically analyzed the correlation between the types of railway accidents and their underlying causes in order to
enhance the overall efficiency of railway safety management. Furthermore, after examining this correlation, the study conducted an
in-depth analysis of how accident causes affect the scale of economic damage. By including a wide range of railway systems?such as
high-speed rail, conventional rail, and urban rail transit?as the subjects of analysis, the research sought to identify, from multiple
perspectives, whether there are statistically significant relationships between accident types and key contributing factors, including
human error, technical failure, and external influences. To this end, data preprocessing and coding were carried out by defining the type
of railway vehicle, the cause of the accident, and the amount of economic damage as nominal variables. A thorough homogeneity of
variance test was then performed to ensure the reliability and validity of the statistical analysis. In addition, a variety of multivariate
statistical techniques were applied to analyze the interaction effects between railway type and accident causes, as well as the resulting
differences in economic losses. The results of this study are expected to serve as a foundational resource for establishing practical
policies to strengthen railway safety management and for developing more precise accident prevention strategies. Furthermore, they
offer meaningful implications for guiding future research in related fields and are anticipated to make a substantial contribution to the
development of customized safety management systems by railway operating agencies. |