Traffic Accident Risk Analysis from Heterogeneous Data
完了
柴崎 亮介
With the rapid development of urbanization and public transportation system, the number of traffic accidents have significantly increased globally over the past decades and become a big problem for human society.To improve traffic safety, government has made transportation policies to rule driver behavior. Another strategy is to add additional infrastructure or to improve the existing road condition. Understanding what causes traffic accidents and implement accident information into risk analysis will help us estimating accident risk efficiently. Recently, a significant change in intelligent transportation systems is that much more data can be collected from a variety of sensors. The availability of heterogeneous data provide us a more valid way to analyze accident from different view. Therefore, we aim to collect accident related data and analyze accident risk more precisely by mining these data with machine learning methods.
変更のために新しい申請を保存します。 This will save a new application on the system for a modification.
申請中の研究者は表示されません。 / Pending researchers are not shown.
柴崎亮介 / 東京大学空間情報科学研究センター
陳 全俊 / 東京大学 工学系研究科
申請中のデータセットは表示されません。 / Pending datasets are not shown.
座標付き電話帳DBテレポイント 法人版（P1B62_2016年2月）
拡張版全国デジタル道路地図データベース 2016年版
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