Fusing moving average model and stationary wavelet decomposition for automatic incident detection: case study of Tokyo Expressway

Q. Liu, Edward Chin Shin Chung, L. Zhai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


© 2014 Periodical Offices of Chang'an UniversityTraffic congestion is a growing problem in urban areas all over the world. The transport sector has been in full swing event study on intelligent transportation system for automatic detection. The functionality of automatic incident detection on expressways is a primary objective of advanced traffic management system. In order to save lives and prevent secondary incidents, accurate and prompt incident detection is necessary. This paper presents a methodology that integrates moving average (MA) model with stationary wavelet decomposition for automatic incident detection, in which parameters of layer coefficient are extracted from the difference between the upstream and downstream occupancy. Unlike other wavelet-based method presented before, firstly it smooths the raw data with MA model. Then it uses stationary wavelet to decompose, which can achieve accurate reconstruction of the signal, and does not shift the signal transfer coefficients. Thus, it can detect the incidents more accurately. The threshold to trigger incident alarm is also adjusted according to normal traffic condition with congestion. The methodology is validated with real data from Tokyo Expressway ultrasonic sensors. Experimental results show that it is accurate and effective, and that it can differentiate traffic accident from other condition such as recurring traffic congestion.
Original languageEnglish
Pages (from-to)404-414
Number of pages11
JournalJournal of Traffic and Transportation Engineering (English Edition)
Issue number6
Publication statusPublished - 1 Dec 2014
Externally publishedYes


  • automatic incident detection
  • moving average model
  • stationary wavelet decomposition
  • Tokyo Expressway

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation

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