Estimating Sudden Braking using Weather Estimation by a Deep Learning Framework from Drive Recorder Data

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  • ZHANG Hanwei
    Graduate School of Information Science and Electrical Engineering, Kyushu University
  • SATO Yuta
    Graduate School of Information Science and Electrical Engineering, Kyushu University
  • KAWASAKI Hiroshi
    Faculty of Information Science and Electrical Engineering, Kyushu University
  • MINE Tsunenori
    Faculty of Information Science and Electrical Engineering, Kyushu University
  • ONO Shintaro
    Institute of Industrial Science, The University of Tokyo

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Other Title
  • ドライブレコーダーデータから深層学習により推定した天候情報を用いた急ブレーキ推定

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Abstract

<p>Data mining based vehicle probe data analysis has addressed many attentions since we have entered the era of big data. In this work, we propose a study of combining probe data with weather information to perform sudden braking estimation using data mining techniques. We train a deep neural network and estimate weather situations from drive recorders in real time. In addition, we also gather information from meteorological observatories to provide further comparisons. Our experimental results show that the usage of weather information have a slight performance improvement over probe data only analysis.</p>

Journal

  • SEISAN KENKYU

    SEISAN KENKYU 73 (2), 131-136, 2021-03-01

    Institute of Industrial Science The University of Tokyo

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