Abstract
The records of 24,797 traffic accidents (9039 involving fatalities or severe injury) during rainy conditions from 2007 to 2017 in Seoul, South Korea, were used to analyze the spatial distribution of the traffic accidents and rainfall events based on radar and gauge rainfall data. According to the spatial correspondence analysis between rainfall distribution and accident locations for localized and stratiform rain events, radar data in a two-dimensional grid (250 by 250 m) of 10 min temporal resolution benefited the localized rainfall distribution concerning the accident location. The relative accident rate (RAR) from radar data, which was used as a quantitative reference value for the effect of rainfall on traffic accidents, was about 18% higher than that from gauge rainfall. The radar data more clearly classified the number of traffic accidents during rainy conditions because its spatial distribution was more precise for all accidents. In addition, the RAR estimation of accidents involving fatalities and severe injury during rainfall could provide information on the district in which traffic accidents increase due to rainfall. The study results support the adoption of radar-derived rainfall data to analyze the influence of rainfall on accidents and the development of more accurate risk-assessment tools for drivers and planners.
Highlights
The number of fatal road accidents increases sharply during adverse weather conditions such as fog, snow, or rain; this trend causes problems including socio-economic loss and increased social anxiety [1,2,3,4]
Based on the number of traffic accidents that occurred under rainy conditions (24,797), the distance between the traffic accident location and closest point of each rainfall data source was analyzed
The use of automatic weather stations (AWSs) locations to assess accident-causing rainfall phenomena is not reliable given the range of distances involved, whereas the high-resolution radar ensures that any given accident location is no more than 183 m from a rainfall data point, resulting in much higher accuracy
Summary
The number of fatal road accidents increases sharply during adverse weather conditions such as fog, snow, or rain; this trend causes problems including socio-economic loss and increased social anxiety [1,2,3,4]. In the Seoul area, the observation network measuring rainfall information is sparse; a limited number of studies have been conducted on the relationship between rain and traffic accidents and its effects [14]. Jaroszweski and McNamara [18] compared the relative accident rate (RAR) for precipitation events using both radar-derived and gauge-based rainfall data for two urban areas in the United Kingdom, finding that the former approach was far superior. Many studies have assessed the cause-and-effect relationship between traffic accidents and rainfall, few have used such time-based high-resolution radar data, especially to analyze changes in the frequency of traffic accidents due to differences in spatial rainfall distribution within urban areas. Korea, using the gauge- and radar-derived rainfall data to assess the influence of the type of rainfall data used on the spatial distribution of traffic accident patterns
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