高速公路气象服务平台研究及应用
发布时间：2018-09-05 08:00
【摘要】：伴随着高速公路智能化服务方向的发展,我国针对高速公路具体应用需求的软硬件研究应用也得到了长足的发展。特别是近些年来,基于实际应用需求的各式各样的传感器的大量研发,为高速公路的智能化服务提供了很好的软硬件条件,进而也促进了整个智能交通的迅速发展。 本文根据高速公路气象服务平台HMSP (Highway Meteorological Service Platform)的具体需求,在研究了目前应用于高速公路智能化服务体系中的各种技术的基础上,针对全国高速公路网庞大的数据采集量,提出基于压缩感知CS (Compressive Sensing)的HMSP数据采集方法。以南京到苏州这段高速公路作为研究基础对象,针对该段高速公路沿线的气象采集点,以软件的形式设计了具有高性能的CS算法,在HMSP采集端通过DCT基实现对数据信号的稀疏化并实现感知测量,同时在数据接收端即本文建立的气象服务云MSC(the Meteorological Service Cloud)中实现了基于OMP(Orthogonal Matching Pursuit)算法的数据信号重构。通过实验仿真证明该方法在实际的运行中大幅度减少了采集点的数据采集量,进而减少了数据的传输量,降低了整个网络的耗能,在保证数据精度的基础上实现了高效节能实时的目标,为高速公路智能化发展提供了一定的理论研究帮助。 针对现阶段高速公路沿线气象采集点传感器分布稀疏的状况,为在增加传感器密度的同时减少数据传输量,进一步提高高速公路沿线气象数据的实时精准性,本文还提出基于CS的HMSP低能耗数据融合方法。以汤山气象站采集点为实验基础,模拟布置小型的路面温度无线传感器网络,在运行改进的LEACH (LowEnergy Adaptive Clustering Hierarchy)算法基础上CH节点(Cluster Head)对簇内节点传来的数据做基于贝叶斯估计的数据融合,实现了低能耗数据融合方法。实验证明该方法的实现不仅进一步减少了数据的传输量,还提高了高速公路沿线气象数据的实时精准性,为高速公路沿线车辆出行获取实时的气象状况提供了很好的帮助。 最后本文将HMSP系统建立于云平台基础上,提出气象服务云MSC的设想,给出HMSP各功能模块的设计简要描述并对HMSP系统主要功能效果进行展示。通过实际数据的测试,HMSP系统的应用开发达到了预期的设计需求,从而为未来高速公路智能化服务的拓展提供了一定的参考价值。
[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.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：P49;U495
本文编号：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.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：P49;U495
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