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Paper details
Number 2 - June 2014
Volume 24 - 2014
A support vector machine with the tabu search algorithm for freeway incident detection
Baozhen Yao, Ping Hu, Mingheng Zhang, Maoqing Jin
Abstract
Automated Incident Detection (AID) is an important part of Advanced Traffic Management and Information Systems
(ATMISs). An automated incident detection system can effectively provide information on an incident, which can help
initiate the required measure to reduce the influence of the incident. To accurately detect incidents in expressways, a
Support Vector Machine (SVM) is used in this paper. Since the selection of optimal parameters for the SVM can improve
prediction accuracy, the tabu search algorithm is employed to optimize the SVM parameters. The proposed model is
evaluated with data for two freeways in China. The results show that the tabu search algorithm can effectively provide
better parameter values for the SVM, and SVM models outperform Artificial Neural Networks (ANNs) in freeway incident
detection.
Keywords
automated incident detection, support vector machine, tabu search, freeway