NDLI: Real time traffic control framework based on simulated human intelligence for emergency evacuation

Content Provider	IEEE Xplore Digital Library
Author	Guiyan Jiang Zhengyan Wu Chunqin Zhang Qiao Li
Copyright Year	2010
Description	Author affiliation: State Key Lab of Automotive Dynamic Simulation, College of Automobile, Jilin University, Changchun, China (Guiyan Jiang) \|\| Traffic Information Engineering and Control, College of Transportation, Jilin University, Changchun, China (Zhengyan Wu; Chunqin Zhang) \|\| Department of Foreign Language and Literature, College of Changcheng, China University of Geosciences, Baoding, Hebei Province, China (Qiao Li)
Abstract	Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on real-time efficient traffic control method for emergency evacuation. This paper, on the foundation of simulated human intelligent control, puts forward a framework of real-time traffic control for emergency evacuation, the characteristic of which integrates a method of feature information acquisition and processing, characteristic pattern set, pattern recognition and control rule set. The work of this paper attempts to optimize the real-time traffic control method in terms of both quality and feasibility.
Starting Page	5196
Ending Page	5200
File Size	576137
Page Count	5
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554888
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Traffic control Humans Intelligent control Artificial neural networks Cognition Roads emergency evacuation engineering of communications and transportation system intelligent control system simulated human real-time
Content Type	Text
Resource Type	Article

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