TY - GEN
T1 - Construction of road anomaly event detection method for occurrences of disasters via state-space model that utilizes weather and probe data
AU - Umeda, Shogo
AU - Kawasaki, Yosuke
AU - Kuwahara, Masao
AU - Iihoshi, Akira
N1 - Funding Information:
This work was supported by the Japan Society for the Promotion of Science KAKENHI (Grant Number 26220906). We thank Honda Motor Co., Ltd. for the probe vehicle data used in this work.
Publisher Copyright:
© 2018 Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018. All rights reserved.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Disaster
KW - Probe Data
KW - Risk Analysis
KW - State Space Model
KW - Time Series Analysis
UR - http://www.scopus.com/inward/record.url?scp=85064662843&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064662843&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85064662843
T3 - Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018
SP - 489
EP - 496
BT - Transportation Systems in the Connected Era - Proceedings of the 23rd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2018
A2 - Gu, Weihua
A2 - Wang, Shuaian
PB - Hong Kong Society for Transportation Studies Limited
T2 - 23rd International Conference of Hong Kong Society for Transportation Studies: Transportation Systems in the Connected Era, HKSTS 2018
Y2 - 8 December 2018 through 10 December 2018
ER -