2016
DOI: 10.1016/j.neucom.2016.06.044
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A traffic flow state transition model for urban road network based on Hidden Markov Model

Abstract: Traffic guidance and prompt information could induce the change of traffic states on road sections, and in turn the effects of these changes will be transited to their relative upstream and downstream sections, which lead to dynamic variations in traffic states of urban regional road networks. In this paper, the rule of dynamic transition in traffic state of urban road networks under the effect of traffic information is studied. Specifically, the hidden Markov model is selected to represent the dynamic transit… Show more

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Cited by 34 publications
(18 citation statements)
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“…Due to its good performance in statistics, HMM (Hidden Markov Model) [21][22][23][24][25] technique is rapidly developed and applied in fields as voice recognition, classification, security situation prediction, intrusion detection, etc. In the field of security situation prediction, Hisham [26] proposed the first HMM model with finite state to predict the multistep attack in cloud computing system.…”
Section: Related Workmentioning
confidence: 99%
“…Due to its good performance in statistics, HMM (Hidden Markov Model) [21][22][23][24][25] technique is rapidly developed and applied in fields as voice recognition, classification, security situation prediction, intrusion detection, etc. In the field of security situation prediction, Hisham [26] proposed the first HMM model with finite state to predict the multistep attack in cloud computing system.…”
Section: Related Workmentioning
confidence: 99%
“…In this theoretical framework, the use of multiple cameras with dissimilar detection errors to detect the flow at one entrance has not been accounted for. The characteristics of the problem above are similar to the classical traffic management problems of queue length estimation upstream of traffic signals and density estimation on highway links, which traffic engineers have been studying for quite some years (e.g., [13][14][15][16][17][18][19]). Many distinct types of filters, such as Kalman Filters, Particle filters, and Hidden Markov Models, have been proposed to improve the estimation of the number of vehicles in a queue and/or on a link in the highway network.…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…This problem further generates traffic accidents, environmental pollution, and energy waste. Urban road networks have been previously studied [36,66,68,69].…”
Section: Introductionmentioning
confidence: 99%