A BASIC STUDY ON TRAFFIC ACCIDENT DATA ANALYSIS USING SUPPORT VECTOR MACHINE

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概要

• 論文の詳細を見る

• In Japan, fatalities from traffic accidents are decreasing, but sacrifices of the traffic accidents are not negligible. So, traffic safety measures are still important. When considering the traffic safety measures, it is effective to extract dangerous locations with high fatality and injury accident rates and then analyze the details of the factors involved in such accidents. Due to numerous factors, however, it is difficult to effectively and efficiently process large quantities of traffic accident data. For this reason, previous traffic analyses are reviewed, and a Support Vector Machine (hereinafter referred to as "SVM"), which has become the focus of attention as a data mining method, is chosen. The SVM is applied to the traffic accident data analysis. The effectiveness of and problems surrounding a SVM are examined in this study. The classification rate of the SVM toward non-learning data was approximately 70%.

• Eastern Asia Society for Transportation Studiesの論文

著者

• TAMURA Tohru

  Dept. of Civil Eng. and Architecture, Muroran Institute of Technology

• HASEGAWA Hironobu

  Division of Civil and Environmental Eng., Muroran Institute of Technology

• FUJII Masaru

  Division of Civil and Environmental Eng., Muroran Institute of Technology

• ARIMURA Mikiharu

  Docon Co., Ltd.

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• A BASIC STUDY ON TRAFFIC ACCIDENT DATA ANALYSIS USING SUPPORT VECTOR MACHINE

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