一種應(yīng)用路阻函數(shù)的路段行駛時(shí)間預(yù)測(cè)方法

1、一種應(yīng)用路阻函數(shù)的路段行駛時(shí)間預(yù)測(cè)方法© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, © 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 1.o摘要：1 2 1 2100039100195© 1994-2013 China Academic Journal Electronic Publishing House. All rig

2、hts reserved, © 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 5%關(guān)鍵詞：A method for short-term road travel time predictionaccording to the road traffic impedance functionCao Hanyang1,2 Shen Li1,2(1 Beijmg Institute of Remote Sensing Equipment, Beijing 100039,Ch

3、nia,2. Beijing Aerospace Fudao High-Tech Co Ltd , Beijing 100195,China)Abstract: The short-term traffic prediction is a technology v/hich combines the theones of traffic and data processing and automatically control. Its researcli target is to predict the future traffic and provide a prefeired road

4、for the travelers For the need of drivers, a method for short-term road travel time prediction is presented, which can predict road travel time before the car veenng into this road. This method is designed based on the road traffic impedance function, and could take advantage of tlie relationship am

5、ong the flow, speed and road travel time The parameters of the predictive function are estimated through LSB According to the test, the results are satisfactoiy, which only used 5% data as sample for the LSB The sample can be renewed timely to update the predictive function, especially when traffic

6、jam taking placeKeywords: ITS short-term traffic prediction road travel time prediction road traffic impedance function1引言1PJP56-75%2路段行駛時(shí)間的數(shù)學(xué)模型2.1預(yù)測(cè)模型的輸入交通參數(shù)2.2路阻函數(shù)岡 Gi-eenshields1963VzVjt = VZkmax1v/ kq廠koQk1Qk -z k-mAx3534© 1994-2013 China Academic Journal Electronic Publishing House. All ri

7、ghts reserved, 2哄:naxqr4cd410V/g嚴(yán)c2410V535© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 3路段行駛時(shí)間預(yù)測(cè)算法3.1預(yù)測(cè)模型的結(jié)構(gòu)1010public RoadsBPRU S Bureau of10二旦Vr爲(wèi)弘+勺）(二)5361V/oJ(0-1 + aq<cjt = t0AC)寺一%)+% 丄11BPR12(弘旳0 + 0)AM*+。（二）心/（二o）+廣（61）/(q-qj+q。1 _ 1、+ o（二）

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9、e. All rights reserved, 心/（二0）+ 廣（二 J/(aqM + 'qm-qJ+gocd1+_+婦181% v/o 丿丿18/(-n h 衛(wèi)%/(-o)"詈+S)#© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, #© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, ARMA19t = t q +

10、h. %亠+也-七抵% %3.2測(cè)試結(jié)果#© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, #© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 19h2 h3力 4h5#© 1994-2013 China Academic Journal Electronic Publishing House. All rights reser

11、ved, #© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, Paramics55%18ParamicsAPI15minParamics15145#© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 20C013.3堵車狀況下的行駛時(shí)間預(yù)測(cè)215min34結(jié)論539© 1994-2013 China Academic Journa

12、l Electronic Publishing House. All rights reserved, 參考文獻(xiàn):5%SVMJ2005,(10):197.1991J 1J? 3rl (J卩】2003.22(4)41-462005.31(8) 35-36#© 1994-2013 China Academic Journal Electronic Publishing House. All rights reserved, 4 Stephen Clark Traffic prediction using multivanate nonparainetnc regressionJJ. Jo

13、urnal of Transportation Engineeiing, 2003,129 1611685 Elam I Vlahogianm. Mattliew G Karlaftis and John C Gohas Optimized and meta-optimized neural networks for short-terratra伍c flow prediction A genetic approach!J Transportation Research Part C Emerging Technologies, 2005, 13(3) 211-2346 Xiao H, Sui

14、i H, Ran B, Oh Y Fuzzy-neural network traffic prediction 丘ame work with wavelet decompositionJ. Transportation Research Record 1836, 2003 16-207 Nam DH Traffic dynanucs method for estimating &eeway travel times in real time from flow measurements!J Journal of Transportation Engineenng 1996. 122(3) 185S Lain SH, To an TD Short-term travel time predictions using support