Incident Alert by an Anomaly Indicator of Probe Trajectories

Masanori Yoshida, Yosuke Kawasaki, Shogo Umeda, Masao Kuwahara

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Herein, we propose methods that use three-dimensional trajectory data (one-dimensional time × two-dimensional space) acquired from probe vehicles to detect damaged spots on roads caused by natural disasters. Detecting road damages immediately after a disaster is essential to ensure quick and safe evacuations, rescue and relief operations, and efficient road repairs. However, road damages are currently monitored only by closed-circuit television, administrators patrolling the roads, and reports from users of the roads. Consequently, the number of locations that are being monitored is limited, and damage detection is delayed. Our proposed methods automatically estimate the locations of widespread damages on general roads. After analyzing and extracting the features of probe data obtained during a disaster, our proposed methods were verified using the data of past disasters. Our methods can identify anomalous vehicle behaviors and indicate various possibilities for detecting road damages.

Original languageEnglish
Pages (from-to)179-186
Number of pages8
JournalTransportation Research Procedia
Volume34
DOIs
Publication statusPublished - 2018
Event6th International Symposium of Transport Simulation, ISTS 2018 and the 5th International Workshop on Traffic Data Collection and its Standardization, IWTDCS 2018 - Matsuyama, Japan
Duration: 2018 Aug 62018 Aug 8

Keywords

  • large-scale disaster
  • probe trajectory data
  • traffic-fault detection

ASJC Scopus subject areas

  • Transportation

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