本文選題：智能交通系統(tǒng) + 小路提取��； 參考：《湖南科技大學(xué)》2014年碩士論文

【摘要】：智能交通系統(tǒng)有利于改善城市交通環(huán)境，合理分配交通資源，可以獲取巨大的經(jīng)濟和社會效益。電子地圖是構(gòu)建智能交通系統(tǒng)的基礎(chǔ)，自動生成電子地圖和及時更新路網(wǎng)信息對于車輛導(dǎo)航、交通規(guī)劃和土地利用等具有重要的應(yīng)用價值和意義。目前大多基于遙感影像的生成方法只是針對某種類型的道路，即該方法的通用性導(dǎo)致了其準確性較差，而且影像更新周期較長使得路網(wǎng)信息難以及時更新。 隨著智能移動終端和移動互聯(lián)網(wǎng)的快速發(fā)展，人們能夠方便地獲取GPS軌跡數(shù)據(jù)。GPS軌跡數(shù)據(jù)具有采集成本低、更新速度快和覆蓋范圍廣等特點。因此，基于GPS軌跡的提取方法引起了學(xué)術(shù)界與產(chǎn)業(yè)界的廣泛關(guān)注。目前，研究者通�；诟榆嚮虺鲎廛嚨腉PS軌跡來挖掘城市主干路網(wǎng)。但是，現(xiàn)有方法忽略了小路的自動提取，而這種小路保有量多且變更頻繁，保障其完整、準確對于抗震救災(zāi)、小區(qū)導(dǎo)航或鄉(xiāng)村游覽等應(yīng)用領(lǐng)域非常重要。 針對該問題，本文提出基于步行GPS軌跡的小路提取方法。實驗數(shù)據(jù)采用湖南科技大學(xué)的步行巡檢GPS數(shù)據(jù)集，該數(shù)據(jù)集是巡檢人員在巡邏過程中由隨身攜帶的GPS記錄儀所記錄，共有1746萬個軌跡點。本文方法主要包括三部分內(nèi)容，分別為數(shù)據(jù)預(yù)處理、道路中心線生成和路網(wǎng)精度評價。首先，通過數(shù)據(jù)預(yù)處理去除原始GPS軌跡數(shù)據(jù)的異常值，確保數(shù)據(jù)的精確性。其次，利用GPS軌跡自動地生成道路中心線，，并進行路網(wǎng)的矢量化處理。最后，以百度地圖等相關(guān)信息為參考路網(wǎng)，分別從定性與定量兩方面對本文方法的路網(wǎng)提取進行評價。其中，道路中心線生成方法包括軌跡點聚類、聚類點分割和中心線擬合三部分。實驗結(jié)果表明，本文方法能夠準確提取路網(wǎng)，覆蓋率可達96.21%，而誤檢率僅3.26%；并且能夠提取小路和更新路網(wǎng)。
[Abstract]:Intelligent Transportation system (its) is beneficial to improve urban traffic environment, allocate traffic resources rationally, and obtain huge economic and social benefits. Electronic map is the basis of constructing intelligent transportation system. Automatic generation of electronic map and timely updating of road network information have important application value and significance for vehicle navigation, traffic planning and land use. At present, most of the methods based on remote sensing image are only for a certain type of road, that is, the generality of this method leads to its poor accuracy, and the long period of image updating makes it difficult to update the road network information in time. With the rapid development of intelligent mobile terminals and mobile Internet, it is easy to obtain GPS trajectory data. GPS trajectory data has the characteristics of low acquisition cost, fast update speed and wide coverage. Therefore, the extraction method based on GPS trajectory has attracted wide attention in academia and industry. At present, researchers usually mine the urban trunk road network based on the GPS tracks of floating cars or taxis. However, the existing methods ignore the automatic extraction of the path, which has a large number and changes frequently, and ensures its integrity, which is very important for the earthquake relief, community navigation or rural tourism and other application fields. To solve this problem, a path extraction method based on walking GPS locus is proposed in this paper. The experimental data are based on the walking GPS data set of Hunan University of Science and Technology. The data set is recorded by the GPS recorder carried by the patrol personnel during the patrol, with a total of 17.46 million locus points. This method includes three parts: data preprocessing, road centerline generation and road network accuracy evaluation. Firstly, the outliers of the original GPS trajectory data are removed by data preprocessing to ensure the accuracy of the data. Secondly, the road centerline is generated automatically by using GPS trajectory, and the vectorization of road network is carried out. Finally, taking Baidu map and other related information as reference road network, this paper evaluates the road network extraction from qualitative and quantitative aspects. Among them, the road centerline generation method includes trajectory point clustering, clustering point segmentation and centerline fitting. The experimental results show that the proposed method can extract the road network accurately, with a coverage rate of 96.21 and a false detection rate of only 3.26 percent, and can extract the path and renew the road network.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P228.4;U495

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本文編號：1945149