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

Volume

2

fYear

0

fDate

0-0 0

Firstpage

8769

Lastpage

8773

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);

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713694

Filename

1713694