Title :
Study on Automated Incident Detection Algorithms for Freeways Based on SVM
Author :
Jiang, Guiyan ; Cai, Zhili ; Gang, Longhui ; Guo, Haifeng
Author_Institution :
Coll. of Transp., Jilin Univ., Changchun
Abstract :
Aimed at the problem that many AID algorithms have lower detection rate and higher false alarming rate, this paper proposed a kind of AID algorithms for freeways based on SVM. The eigenvector reflecting traffic state was designed according to selected traffic measures that can be provided by many kinds of traffic sensors. AID algorithms were designed based on different sorts of SVM models and tested and compared with simulated data. The results showed that the performances of proposed methods are better than selected classic AID algorithms
Keywords :
automated highways; eigenvalues and eigenfunctions; road safety; support vector machines; automated incident detection; eigenvector; freeways; intelligent transportation systems; support vector machine; traffic sensors; traffic state; Algorithm design and analysis; Automation; Detection algorithms; Educational institutions; Intelligent control; Support vector machines; Testing; Traffic control; Transportation; Automated Incident Detection (AID); Freeway; Intelligent Transportation Systems (ITS); Support Vector Machine (SVM);
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713694
