基于自适应加权平均的车速检测研究
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摘要
随着智能交通的发展,海量的交通状态实时数据成为智能交通的研究对象,利用低损耗获取高实时性的交通流状态成为实际应用研究中的重点.本文引入一种自适应加权平均的车速检测方法,与以往的方法相比,自适应加权平均方法更加简单,并且容易实现;虽然其误差比最小均方差加权平均算法略大,但是这种方法不必以存储海量的交通信息数据为代价,解决了交通信息采集过程中的关键——实时性不高、存储容量大等实际问题.通过MATLAB仿真结果可以看到,此方法大大节省了数据存储空间和数据处理的时间,适合在实际工程应用中广泛推广.
With the development of intelligent transportation systems(ITS),the magnanimity real-time traffic data become a major study objectivities,and the key is how to get high quality real-time traffic information with low loss.An adaptive weighted average method for detecting speed is introduced in this paper.Compared with traditional approaches,this method is easier to implement,and the error is slightly larger than the minimum mean square error weighted average.This method does not need large storage space for traffic information,which can resolve the problem of real-time in the course of measuring the traffic parameters.The result of the MATLAB simulation shows that this method saves not only hardware but time.it matches well with the actual demand.
With the development of intelligent transportation systems(ITS),the magnanimity real-time traffic data become a major study objectivities,and the key is how to get high quality real-time traffic information with low loss.An adaptive weighted average method for detecting speed is introduced in this paper.Compared with traditional approaches,this method is easier to implement,and the error is slightly larger than the minimum mean square error weighted average.This method does not need large storage space for traffic information,which can resolve the problem of real-time in the course of measuring the traffic parameters.The result of the MATLAB simulation shows that this method saves not only hardware but time.it matches well with the actual demand.
引文
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[9]滕召胜.基于自适应加权数据融合的粮食水分快速测定议[J].农业机械学报,1999,30(6):64-67.[TENG Z S.An intelligent instrument for quickmeasurement of cereal moisture content based on self-adaptive fusion of weighted data[J].Transactions ofthe Chinese Society of Agricultural Machinery,1999,30(6):64-67.]
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[2]钱哨,张云鹏,黄少波.智能交通云:基于云计算的智能交通系统[J].计算机与现代化,2010,(11):183-186.[QIAN S,ZHANG Y P,HUANG S B.Intelligent transport cloud:ITS based on cloudcomputing[J].Computer and Modernization,2010,(11):183-186.]
[3]郭军杰,闫茂德,陈荫三.高速公路网异构GIS-T信息共享的本体模型[J].交通运输工程学报,2011,11(1):107-113.[GUO J J,YAN M D,CHEN Y S.Ontology model of information sharing forheterogeneous GIS-T in freeway network[J].Journal ofTraffic and Transportation Engineering,2011,11(1):107-113.]
[4]童小华,程效军,刘世杰,等.基于J2EE高速公路网络地理信息系统平台研究[J].同济大学学报,2006,34(12):1627-1631.[TONG X H,CHENG X J,LIU S J,et al.Development of J2EE and WebGISbased highway management system[J].Journal ofTongji University(Natural Science),2006,34(12):1627-1631.]
[5]曾滢,杨晓光,马莹莹.交叉口动态车道功能与信号控制协同问题研究[J].同济大学学报,2009,37(7):903-908.[ZENG Y,YANG X G,MA Y Y.Studyon synergy problem of dynamic lane-use assignmentand signal control at intersections[J].Journal ofTongji University(Natural Science),2009,37(7):903-908.]
[6]杨兆升,杨庆芳,冯金巧.路段平均速度组合融合算法及其应用[J].吉林大学学报,2004,34(4):675-678.[YANG Z S,YANG Q F,FENG J Q.Combinedtime-space average speed information fusion algorithmand its application[J].Journal of Jilin University,2004,34(4):675-678.]
[7]杨兆升,王爽,马道松.基础交通信息融合方法综述[J].公路交通科技,2006,23(3):111-116.[YANGZ S,WANG S,MA D S.Review of basic traffic datafusion methods[J].Journal of Highway andTransportation Research and Development,2006,23(3):111-116.]
[8]瞿翌立,戴逸松.多传感器数据自适应加权融合估计算法的研究[J].计量学报,1998,19(1):69-75.[ZHUO L L,DAI,Y S.Study of adaptive weightedfusion estimated algorithm of multisensor data[J].ACTA Metrologica Sinica,1998,19(1):69-75.]
[9]滕召胜.基于自适应加权数据融合的粮食水分快速测定议[J].农业机械学报,1999,30(6):64-67.[TENG Z S.An intelligent instrument for quickmeasurement of cereal moisture content based on self-adaptive fusion of weighted data[J].Transactions ofthe Chinese Society of Agricultural Machinery,1999,30(6):64-67.]
[10]刘智勇.智能交通控制理论及其应用[M].科学出版社,2003年.[LIU Z Y.Intelligent traffic controltheory and application[M].Science PublishingCompany,2003.]
[11]Bataillou E,Thierry E,Rix H.Weighted averaging withadaptive weight estimation[J].Computers inCardiology,1991.Proceedings.23-26 Sept.1991:37-40.
[12]Yager R R,Filev D P.Induced ordered weightedaveraging operators[J].Systems,Man,andCybernetics,Part B:Cybernetics IEEE Transactionson,1999,29(2):141-150.
[13]Christopher A Vaz,N V Thakor.Adaptive Fourierestimation of time-varying evoked potentials[J].IEEETransaction on Biomedical Engineering,1989,36(4):448-455.