DocumentCode :
1814413
Title :
A new algorithm of incident detection on freeways
Author :
Wen, Huimin ; Yang, Zhaosheng ; Jiang, Guiyan ; Shao, Changfeng
Author_Institution :
Coll. of Transp., Jilin Univ., China
fYear :
2001
fDate :
2001
Firstpage :
197
Lastpage :
202
Abstract :
With the high development speed of the Chinese economy, lots of new freeways have been constructed. Hence, incident management becomes an important issue in the freeway traffic management system. Because incident detection is a kind of pattern recognition problem, in this paper we employed the probabilistic neural network (PNN) to solve it. Applying traffic simulation software FRESIM, a wide range of incidents that include different patterns under a variety of flow conditions and traffic periods were generated to train and evaluate the performance and the transferability of the proposed PNN-based algorithm. It was proved that the models of our proposed algorithm built on one segment can be used for other segments, and all three performance measures indicated the potential of practical use of them
Keywords :
automated highways; learning (artificial intelligence); neural nets; pattern recognition; road traffic; traffic engineering computing; FRESIM traffic simulation software; flow conditions; freeway incident detection; freeway incident management; freeway traffic management system; neural net training; pattern recognition problem; probabilistic neural network; traffic periods; Disaster management; Educational institutions; Neural networks; Pattern recognition; Road accidents; Road safety; Road transportation; Telecommunication traffic; Traffic control; Vehicle safety;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicle Electronics Conference, 2001. IVEC 2001. Proceedings of the IEEE International
Conference_Location :
Tottori
Print_ISBN :
0-7803-7229-8
Type :
conf
DOI :
10.1109/IVEC.2001.961753
Filename :
961753
Link To Document :
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