Title :
Identification method of traffic state based on cloud theory
Author :
Gao, Hongyan ; Liu, Fasheng
Author_Institution :
Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
Abstract :
Traffic state identification is a key technology of dynamic guidance system. In view of the fuzziness and randomness of traffic state, this paper develops an algorithm of traffic state identification based on cloud theory. According to synthesized cloud theory, the synthesized evaluation cloud model is established by integrating clouds of different evaluation factors. Using x condition cloud generator and maximal decision method, the synthesized identified cloud model is built. Finally, the cloud similarity between the synthesized evaluation cloud and the synthesized identified cloud decides the identification results. The experiment results show that it is feasible and can be easily implemented.
Keywords :
fuzzy set theory; road traffic; cloud similarity; cloud theory; dynamic guidance system; maximal decision method; synthesized evaluation cloud model; traffic state identification; Artificial intelligence; Artificial neural networks; Clouds; Entropy; Helium; Intelligent transportation systems; Random number generation; Telecommunication traffic; Traffic control; Uncertainty; cloud similarity; synthesized cloud; traffic state identification;
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
DOI :
10.1109/ICACC.2010.5487206