高速公路氣象服務(wù)平臺研究及應(yīng)用
發(fā)布時間：2018-09-05 08:00
【摘要】：伴隨著高速公路智能化服務(wù)方向的發(fā)展,我國針對高速公路具體應(yīng)用需求的軟硬件研究應(yīng)用也得到了長足的發(fā)展。特別是近些年來,基于實際應(yīng)用需求的各式各樣的傳感器的大量研發(fā),為高速公路的智能化服務(wù)提供了很好的軟硬件條件,進(jìn)而也促進(jìn)了整個智能交通的迅速發(fā)展。 本文根據(jù)高速公路氣象服務(wù)平臺HMSP (Highway Meteorological Service Platform)的具體需求,在研究了目前應(yīng)用于高速公路智能化服務(wù)體系中的各種技術(shù)的基礎(chǔ)上,針對全國高速公路網(wǎng)龐大的數(shù)據(jù)采集量,提出基于壓縮感知CS (Compressive Sensing)的HMSP數(shù)據(jù)采集方法。以南京到蘇州這段高速公路作為研究基礎(chǔ)對象,針對該段高速公路沿線的氣象采集點,以軟件的形式設(shè)計了具有高性能的CS算法,在HMSP采集端通過DCT基實現(xiàn)對數(shù)據(jù)信號的稀疏化并實現(xiàn)感知測量,同時在數(shù)據(jù)接收端即本文建立的氣象服務(wù)云MSC(the Meteorological Service Cloud)中實現(xiàn)了基于OMP(Orthogonal Matching Pursuit)算法的數(shù)據(jù)信號重構(gòu)。通過實驗仿真證明該方法在實際的運行中大幅度減少了采集點的數(shù)據(jù)采集量,進(jìn)而減少了數(shù)據(jù)的傳輸量,降低了整個網(wǎng)絡(luò)的耗能,在保證數(shù)據(jù)精度的基礎(chǔ)上實現(xiàn)了高效節(jié)能實時的目標(biāo),為高速公路智能化發(fā)展提供了一定的理論研究幫助。 針對現(xiàn)階段高速公路沿線氣象采集點傳感器分布稀疏的狀況,為在增加傳感器密度的同時減少數(shù)據(jù)傳輸量,進(jìn)一步提高高速公路沿線氣象數(shù)據(jù)的實時精準(zhǔn)性,本文還提出基于CS的HMSP低能耗數(shù)據(jù)融合方法。以湯山氣象站采集點為實驗基礎(chǔ),模擬布置小型的路面溫度無線傳感器網(wǎng)絡(luò),在運行改進(jìn)的LEACH (LowEnergy Adaptive Clustering Hierarchy)算法基礎(chǔ)上CH節(jié)點(Cluster Head)對簇內(nèi)節(jié)點傳來的數(shù)據(jù)做基于貝葉斯估計的數(shù)據(jù)融合,實現(xiàn)了低能耗數(shù)據(jù)融合方法。實驗證明該方法的實現(xiàn)不僅進(jìn)一步減少了數(shù)據(jù)的傳輸量,還提高了高速公路沿線氣象數(shù)據(jù)的實時精準(zhǔn)性,為高速公路沿線車輛出行獲取實時的氣象狀況提供了很好的幫助。 最后本文將HMSP系統(tǒng)建立于云平臺基礎(chǔ)上,提出氣象服務(wù)云MSC的設(shè)想,給出HMSP各功能模塊的設(shè)計簡要描述并對HMSP系統(tǒng)主要功能效果進(jìn)行展示。通過實際數(shù)據(jù)的測試,HMSP系統(tǒng)的應(yīng)用開發(fā)達(dá)到了預(yù)期的設(shè)計需求,從而為未來高速公路智能化服務(wù)的拓展提供了一定的參考價值。
[Abstract]:With the development of highway intelligent service direction, the research and application of software and hardware for expressway application in China has been greatly developed. Especially in recent years, a large number of sensors based on practical application requirements have provided a good software and hardware conditions for the intelligent service of highway, and also promoted the rapid development of the whole intelligent transportation. In this paper, according to the specific demand of the expressway meteorological service platform HMSP (Highway Meteorological Service Platform), based on the research of various technologies used in the highway intelligent service system, the paper aims at the huge data collection amount of the national highway network. A HMSP data acquisition method based on compressed sensing CS (Compressive Sensing) is proposed. Taking the expressway from Nanjing to Suzhou as the basic research object, a high performance CS algorithm is designed in the form of software for the meteorological collection points along the highway. At the HMSP acquisition end, the data signal is sparse and the perceptual measurement is realized through the DCT basis. At the same time, the data signal reconstruction based on the OMP (Orthogonal Matching Pursuit) algorithm is realized in the meteorological service cloud MSC (the Meteorological Service Cloud), which is built in the data receiving terminal. The experimental results show that the method can greatly reduce the amount of data acquisition at the acquisition point, thus reduce the amount of data transmission and reduce the energy consumption of the whole network. On the basis of ensuring the precision of data, the goal of high efficiency and energy saving in real time is realized, which provides a certain theoretical research help for the intelligent development of freeway. In view of the sparse distribution of sensors in meteorological data collection points along expressway at present, in order to increase the density of sensors and reduce the amount of data transmission, and further improve the real-time accuracy of meteorological data along the highway, This paper also proposes a low energy HMSP data fusion method based on CS. Based on the collected points of Tangshan weather station, a small wireless sensor network of road surface temperature is simulated and arranged. On the basis of running the improved LEACH (LowEnergy Adaptive Clustering Hierarchy) algorithm, the (Cluster Head) of CH node makes the data fusion based on Bayesian estimation to the data from the cluster nodes, and realizes the low energy consumption data fusion method. Experiments show that the method not only reduces the amount of data transmission, but also improves the real-time accuracy of meteorological data along the highway, and provides a good help for the vehicles along the highway to obtain real-time meteorological conditions. Finally, based on the cloud platform, this paper puts forward the idea of cloud MSC for meteorological service, gives a brief description of the design of each function module of HMSP and shows the main function effect of HMSP system. The application and development of HMSP system based on actual data can meet the expected design requirements, thus providing a certain reference value for the expansion of intelligent highway service in the future.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P49;U495
本文編號：2223670
[Abstract]:With the development of highway intelligent service direction, the research and application of software and hardware for expressway application in China has been greatly developed. Especially in recent years, a large number of sensors based on practical application requirements have provided a good software and hardware conditions for the intelligent service of highway, and also promoted the rapid development of the whole intelligent transportation. In this paper, according to the specific demand of the expressway meteorological service platform HMSP (Highway Meteorological Service Platform), based on the research of various technologies used in the highway intelligent service system, the paper aims at the huge data collection amount of the national highway network. A HMSP data acquisition method based on compressed sensing CS (Compressive Sensing) is proposed. Taking the expressway from Nanjing to Suzhou as the basic research object, a high performance CS algorithm is designed in the form of software for the meteorological collection points along the highway. At the HMSP acquisition end, the data signal is sparse and the perceptual measurement is realized through the DCT basis. At the same time, the data signal reconstruction based on the OMP (Orthogonal Matching Pursuit) algorithm is realized in the meteorological service cloud MSC (the Meteorological Service Cloud), which is built in the data receiving terminal. The experimental results show that the method can greatly reduce the amount of data acquisition at the acquisition point, thus reduce the amount of data transmission and reduce the energy consumption of the whole network. On the basis of ensuring the precision of data, the goal of high efficiency and energy saving in real time is realized, which provides a certain theoretical research help for the intelligent development of freeway. In view of the sparse distribution of sensors in meteorological data collection points along expressway at present, in order to increase the density of sensors and reduce the amount of data transmission, and further improve the real-time accuracy of meteorological data along the highway, This paper also proposes a low energy HMSP data fusion method based on CS. Based on the collected points of Tangshan weather station, a small wireless sensor network of road surface temperature is simulated and arranged. On the basis of running the improved LEACH (LowEnergy Adaptive Clustering Hierarchy) algorithm, the (Cluster Head) of CH node makes the data fusion based on Bayesian estimation to the data from the cluster nodes, and realizes the low energy consumption data fusion method. Experiments show that the method not only reduces the amount of data transmission, but also improves the real-time accuracy of meteorological data along the highway, and provides a good help for the vehicles along the highway to obtain real-time meteorological conditions. Finally, based on the cloud platform, this paper puts forward the idea of cloud MSC for meteorological service, gives a brief description of the design of each function module of HMSP and shows the main function effect of HMSP system. The application and development of HMSP system based on actual data can meet the expected design requirements, thus providing a certain reference value for the expansion of intelligent highway service in the future.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P49;U495
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 楊亞新,范德新;建立高速公路氣象災(zāi)害實時監(jiān)測與決策服務(wù)系統(tǒng)的設(shè)想[J];公路;2003年07期
2 李曉明;原聯(lián)邦德國公路氣象信息系統(tǒng)考察報告[J];國外公路;1997年05期
3 陳敬;;關(guān)于高速公路氣象信息采集系統(tǒng)的研究分析[J];交通節(jié)能與環(huán)保;2012年03期
4 石磊;;冰雪條件下高速公路氣象檢測與預(yù)警系統(tǒng)研究[J];公路交通科技(應(yīng)用技術(shù)版);2012年09期
5 張振維,李巍,蓋永剛;沈大高速公路沿線氣象因子特征研究[J];環(huán)境保護(hù)科學(xué);2000年01期
6 戴瓊海;付長軍;季向陽;;壓縮感知研究[J];計算機學(xué)報;2011年03期
7 車春江;袁成松;;高速公路路面高溫拋物線統(tǒng)計模型[J];中國交通信息產(chǎn)業(yè);2010年04期
8 尹宗康;賀國君;韓斐迪;;基于GPRS無線網(wǎng)絡(luò)的可變信息情報板系統(tǒng)[J];中國交通信息產(chǎn)業(yè);2010年05期
9 錢哨;張云鵬;黃少波;;智能交通云:基于云計算的智能交通系統(tǒng)[J];計算機與現(xiàn)代化;2010年11期
10 韋棟;高速公路霧區(qū)設(shè)置自動限速標(biāo)志系統(tǒng)的探討[J];林業(yè)科技情報;2002年03期
，本文編號：2223670
本文鏈接：http://sikaile.net/kejilunwen/jiaotonggongchenglunwen/2223670.html
最近更新
教材專著
