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Automatic Classification of Traffic Accident Using Velocity and Acceleration Data of Drive Recorder

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 240)

Abstract

In recent years, a drive recorder becomes common and is installed in a car to record sensor data, such as images, acceleration, and speed, about driving. The recorded data is useful to confirm and analyze a dangerous driving scene of a traffic accident and an incident. However, analyzing such data takes long time because it is done by a person who checks data one by one. Therefore, a method of automatic classification of drive recorder data is explored in this study. First, we labeled three types of incidents on the recorded data. Then, after extracting features from the acceleration and velocity, machine learning techniques are applied for the classification. Our preliminary evaluation showed that the classification result achieved about 0.55 of f-measure value.

Keywords

  • Acceleration
  • Classification
  • Machine learning
  • Drive recorder

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Correspondence to Moe Miyata .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Miyata, M., Matsuo, K., Omura, R. (2018). Automatic Classification of Traffic Accident Using Velocity and Acceleration Data of Drive Recorder. In: Murao, K., Ohmura, R., Inoue, S., Gotoh, Y. (eds) Mobile Computing, Applications, and Services. MobiCASE 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-90740-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-90740-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90739-0

  • Online ISBN: 978-3-319-90740-6

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