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Based On Fuzzy Control Theory, Intelligent Traffic Detection And Control

Posted on:2006-10-22Degree:MasterType:Thesis
Country:ChinaCandidate:L D ZhangFull Text:PDF
GTID:2192360155966952Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
Fuzzy control is a kind of artificial intelligent control . It needs no accurate mathematical or physical model. It can be implenented with expert knowledge and human experience, and can satisfy real-time, dynamic control requirement. It has flouring prospect and wide area of application. Since Greek scholar C.P.Pappis and English Fuzzy Control expert E.H.Mamdani set forth Single Intersection Fuzzy Traffic Control in 1977, fuzzy control method has been recognized quickly. From then on, much research was mainly concentrated on single intersection with two-phase traffic control, while research on single intersection with multi-phase and on traffic artery was little. Based on consideration above, My paper mainly solved following problems: 1 Muti-phase fuzzy control and simulation of a Single interrsectionTaking a common road intersection for example, under the consideration of traffic diffluence and traffic conflict, it is much more reasonable to control crossing traffic with four phases. Take current traffic phase detecting cars and next traffic phase detecting cars as fuzzy controller' s input variables, and current phase green light time extension as output variable. So traffic control can be realized with real-time collecting data. Computer simulation results showed that this kind of method was superior to regular fixed-time control and two-phase control. 2 Artery traffic control research and simulationI chose three parameters —Cycle, Split and Offset as the control parameters. The basic thought is to set all traffic artery intersections have the same signal cycle, which was calculated by Webster' s cycle formula based on traffic flow. Each intersection' s split was determined by chaos predicting of coming traffic cars rate. And offset was inferred from roadcars occupation with a Fuzzy Controller. The offset Fuzzy Controller took road cars occupation as input variable, and offset extending time as output variable. Simulation showed that this kind of control had its advantage over regular control. Another feature of my paper is that the main simulation is based on VC++6.0 computer language, not on static Matlab data. This simulation software is perceivable and friendly. User can easily operate many kinds of traffic control. Property dialog will show you whether your control is excellent.
Keywords/Search Tags:ITS Fuzzy Control, Trunk road traffic, Cycle Split, Phase Offset, CarsOccupation Rate, Computer Simulation
PDF Full Text Request
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