Title :
Application of multiple SVM classifier fusion technique in freeway automatic incident detection
Author :
Zhili, Cai ; Guiyan, Jiang
Author_Institution :
Shandong Jiaotong Univ., Jinan
Abstract :
Based on stating the principle of support vector machine (SVM) classifier, this paper analyses the data collected traits by fixed detectors and the traffic characteristics of freeway chiefly. Also, this paper proposes traffic pattern eigenvectors by data of several continuous time intervals for the single traffic parameter, puts forward multiple SVM classifier fusion models and operation flow, as well as analyzing results after simulation.
Keywords :
pattern classification; sensor fusion; support vector machines; traffic engineering computing; freeway automatic incident detection; multiple SVM classifier fusion technique; support vector machine classifier; traffic pattern eigenvectors; Analytical models; Data analysis; Detectors; Educational institutions; Electronic mail; Pattern analysis; Support vector machine classification; Support vector machines; Traffic control; Transportation; AID; Data fusion; Freeway; SVM; SVM Classifier;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605683