Construction of road anomaly event detection method for occurrences of disasters via state-space model that utilizes weather and probe data

Shogo Umeda, Yosuke Kawasaki, Masao Kuwahara, Akira Iihoshi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this research we propose a method to detect road abnormality events (standstill) in the event of natural disasters, using weather data and probe data. The proposed method compares the predicted value by the state space model with the filtered estimator and detects abnormality when the deviation is large. The proposed method was applied to cases of standstill at heavy snow occurring in Fukui and Tokyo, and showed that abnormality can be detected before standstill happening. In addition, we compare the accuracy of abnormality detection between the proposed method and the conventional time series model, and the proposed method has higher prediction accuracy.

Original languageEnglish
Title of host publicationTransportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018
EditorsWeihua Gu, Shuaian Wang
PublisherHong Kong Society for Transportation Studies Limited
Pages489-496
Number of pages8
ISBN (Electronic)9789881581471
Publication statusPublished - 2018 Jan 1
Event23rd International Conference of Hong Kong Society for Transportation Studies: Transportation Systems in the Connected Era, HKSTS 2018 - Hong Kong, Hong Kong
Duration: 2018 Dec 82018 Dec 10

Publication series

NameTransportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018

Conference

Conference23rd International Conference of Hong Kong Society for Transportation Studies: Transportation Systems in the Connected Era, HKSTS 2018
CountryHong Kong
CityHong Kong
Period18/12/818/12/10

Keywords

  • Disaster
  • Probe Data
  • Risk Analysis
  • State Space Model
  • Time Series Analysis

ASJC Scopus subject areas

  • Transportation

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  • Cite this

    Umeda, S., Kawasaki, Y., Kuwahara, M., & Iihoshi, A. (2018). Construction of road anomaly event detection method for occurrences of disasters via state-space model that utilizes weather and probe data. In W. Gu, & S. Wang (Eds.), Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018 (pp. 489-496). (Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018). Hong Kong Society for Transportation Studies Limited.