›› 2012, Vol. 42 ›› Issue (05): 1191-1197.

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Automatic incident detection algorithms fusion method based on factor analysis and cluster analysis

LI Qi1, JIANG Gui-yan1,2, YANG Ju-fen1   

  1. 1. College of Transportation, Jilin University, Changchun 130022, China;
    2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
  • Received:2011-10-26 Online:2012-09-01 Published:2012-09-01

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Abstract: For the improvement of the effect of incident detection using the single automatic incident detection algorithm (AIDA), a set of indexes used for traffic condition on-line evaluating was designed based on the analysis of the causes of failed alarms and false alarms generated by AIDAs used, and an AIDAs fusion method based on factor analysis and cluster analysis was developed. The proposed method was verified and compared using the data collected from the inductive loops on a metropolitan urban freeway. The results showed that under the condition of aimed false alarm rate 0.5% and the detection rates of the original AIDA 63.5 %~66.1%, the detection rate of proposed method is 90.6% and its false alarm rate is only 0.0981%, being obviously better than the contrast methods.

Key words: engineering of communication and transportation system, automatic incident detection, information fusion, factor analysis, cluster analysis

CLC Number: 

  • U491
[1] Luk J Y K, Sin F Y C. The calibration of freeway incident detection algorithms. Australian Road Research Board Working Document No. WD TE 92/001, ARRB, Vermont South, Victoria, 1992.
[2] Chassiakos A, Stephanedes Y. Smoothing algorithms for incident detection//Transportation Research Record 1394, Transportation Research Board, Washington, DC, 1993.
[3] Thomas K, Dia H. Development and evaluation of fractal dimension models for freeway incident detection[J]. Road and Transport Research Journal, 2004, 13 (2): 2-20.
[4] Han S I, Ritchie S G. Statistical and neural classifiers to detect traffic operational problems on urban arterials[J]. Transportation Research Part C, Emerging Technologies, 1998, 6(5): 291-314.
[5] Stephanedes Y J, Hourdakis J. Transferability of freeway incident detection algorithms//Transportation Research Record 1554, Transportation Research Board, Washington, DC, 1996.
[6] Jin X, Cheu R L,Srinivasan D. Development and adaptation of constructive probabilistic neural network in freeway incident detection[J]. Transportation Research Part C: Emerging Technologies, 2002, 10(2): 121-147.
[7] Zhou D S. An integrated traffic incident detection model. USA, Austin: University of Texas Austin at Austin, 2000.
[8] Lein L A. A Boolean algebra approach to multiple sensor voting fusion[J]. IEEE Trans, Aerospace and Electron Sys, 1993, 29(2): 1-11.
[9] Mak C L, Fan H S L. Algorithm fusion for detecting incidents on Singapore's central expressway[J]. Journal of Transportation Engineering, 2006, 132 (4): 321-330.
[10] 覃频频. 基于信息融合的高速公路事件检测建模与仿真. 成都:西南交通大学, 2007. Qin Pin-pin. Modeling and simulation of freeway incident detection based on information fusion. Chengdu: Southwest Jiaotong University, 2007.
[11] 薛薇. SPSS统计分析方法及应用[M]. 北京:电子工业出版社, 2004.
[12] Dudek C L, Messer C J, Nuckles N B. Incident detection on urban freeways//Transportation Research Board, Washington DC: TRB, 1974.
[13] Parkanyi E, Xie C. A complete review of incident detection algorithms and their deployment: what works and what doesn't. Technical Report NETCR37, New England Transportation Consortium, 2005.
[14] Cheu Ruey L, Rithie Stephen G. Automated detection of lane-blocking freeway incidents using artificial neural networks[J].Transportation Research Part C, 1995,3(6):371-378.
[15] 姜桂艳,郭海锋,吴超腾. 基于感应线圈数据的城市道路交通状态判别方法[J]. 吉林大学学报: 工学版, 2008, 38(增刊): 37-42. Jiang Gui-yan, Guo Hai-feng, Wu Chao-teng. Identification method of urban road traffic conditions based on inductive coil data[J]. Journal of Jilin University(Engineering and Technology Edition), 2008, 38(Sup.): 37-42.
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