• Title/Summary/Keyword: Traffic Accident Categorization

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Study on the Establishment of Tollgate Improvement Measures through Categorization of Expressway Tollgate Accidents and Network Clustering (고속도로 톨게이트 교통사고 유형화 및 네트워크 클러스터링 기반 톨게이트 개선방안 수립 연구)

  • Inyoung Kim;Hansol Jeong;Sangmin Park;Kwangseob, Lee;Ilsoo Yun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.5
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    • pp.1-17
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    • 2024
  • In Korea, tollgates are designed in a complex manner with the coexistence of Hi-Pass and Toll Collection System lanes, frequently leading to traffic accidents. Despite the continuous efforts of the government to improve tollgates based on an analysis of accident factors, incidents still persist. Tollgates require drivers to be aware of numerous circumstances and events within a short distance, necessitating careful consideration of several factors and circumstances when analyzing traffic accidents. Therefore, this study applied the Term Frequency-Inverse Document Frequency method to traffic accident data to identify the factors and circumstances. Subsequently, the tollgate traffic accidents were categorized. Finally, effective tollgate improvement measures were proposed based on the categorization result.

Categorization of Traffic Type According to Seoul-City Administrative District Using Cluster Analysis (군집분석을 이용한 서울시 행정구역별 교통유형 분류)

  • Han, Mahn-Seob;Oh, Heung-Un
    • International Journal of Highway Engineering
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    • v.14 no.4
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    • pp.133-140
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    • 2012
  • PURPOSES : Traffic situation of Seoul City is different each administrative district. because each administrative district population, average travel speed, etc are different. thus, regionally differentiated policy is necessary. METHODS : In this study, first, it is to implement the cluster analysis using the traffic factor of twenty-five administrative districts in Seoul, categorize it into the cluster and understand the properties. second, related factors of speed were derived. and method to increase the speed was investigated. we choose the eleven traffic factors such as the number of traffic accident cases, total length, speed, the number of cross section, the number of cross section per km, the rate of roads, registered cars, population attending office and school, population density, area. RESULTS : In the results, first, we could categorize the Seoul-City administrative district into three clusters. in order to find Factors associated with speed a simple regression analysis was performed. and the number of intersections per km is closely related to the speed. CONCLUSIONS : Through this study, transportation policies reflecting local traffic-related characteristics are required.