Title: Prediction of Road Safety Using Road/Traffic Big Data

Year of Publication: Oct - 2015
Page Numbers: 23-27
Authors: Kyusoo Chong, Hongki Sung
Conference Name: The International Conference on Semantic Web Business and Innovation (SWBI2015)
- Switzerland


In reflection of road expansion and increasing use rates, interest has increased in securing road safety. In addition, as natural disasters and calamities in cities are occurring more frequently than before, the necessity of systems and technologies to predict traffic information for safety is also emphasized. Accordingly, this study aims to investigate the technology of road safety prediction based on road big data. This study examines actual cases of road management systems and road safety analysis technologies, Korea and other countries. The types and usability of road information collected through a road management system are analyzed. Based on the result, the limitations of existing technologies and road management systems are analyzed. A number of related technologies and road management systems were examined using based on basic physical information such as distance, speed, etc. and past event information, and they do not reflect various specific factors and real-time data. Accordingly, it is necessary to develop technology for road/traffic information service that utilizes various real-time data sets such as traffic information, climate information, and road condition information as well as analyzes multiple data sets comprehensively. In This study, the utilization of real-time data derived from Korea road management system were investigated and a direction for road safety analysis and traffic information service is also suggested. It will be possible to develop more reliable road safety analysis and management systems and technologies using road data derived from various type of Korea road management systems.