本文關(guān)鍵詞： 浮動車 地圖匹配 權(quán)重 拓撲結(jié)構(gòu) 全球定位系統(tǒng)　出處：《武漢理工大學》2013年碩士論文　論文類型：學位論文

【摘要】：地圖匹配(Map Matching)是一種廣泛應用于導航系統(tǒng)定位的修正方法,這種方法是以軟件技術(shù)為基礎(chǔ)的,通過算法模型將GPS終端設(shè)備獲取的車輛行駛軌跡與實地圖中的拓撲道路關(guān)聯(lián)起來,并修正車輛在實地圖的相對行駛位置。由于地圖匹配在交通系統(tǒng)中有相當大的實用性,很多學者花費大量的時間進行了研究,提出了很多與地圖匹配相關(guān)的算法,這些算法各有優(yōu)劣。能否減少導航系統(tǒng)定位的誤差直接體現(xiàn)了地圖匹配算法性能的好壞,但算法的實時性和魯棒性也不容忽視。由于現(xiàn)有的地圖匹配算法大多只考慮算法自身,導致算法實用性相對不強,所以應該考慮將其他可以有效利用的元素融合到算法中以提高算法的實用性�？偠灾�,在設(shè)計地圖匹配算法的過程中,比較多種算法的優(yōu)缺點,并將這些算法有效地結(jié)合起來,最終實現(xiàn)具有較高實時性、魯棒性以及匹配精度的地圖匹配算法。 本文分析了影響地圖匹配算法匹配精度的因素,并對現(xiàn)有的地圖匹配算法進行了一系列的研究與總結(jié),在此基礎(chǔ)上,提出一個以道路網(wǎng)的拓撲特性為前提,利用當前車輛行駛位置的經(jīng)緯度、行駛方向等信息與電子地圖進行匹配的匹配算法。本論文提出的算法的基本思想是通過對電子地圖進行網(wǎng)格劃分來確定GPS定位點的網(wǎng)格編號,再通過構(gòu)建誤差區(qū)域來縮小匹配的搜索范圍,從而減少了候選匹配路段數(shù),最后構(gòu)建了一個匹配模型,用來計算GPS定位點與候選匹配路段的匹配度,該模型即為權(quán)重模型。該權(quán)重模型是通過計算GPS定位點與候選匹配路段的最短距離、GPS定位點的行駛方向與候選匹配路段的夾角、定位點與候選匹配路段的相對位置關(guān)系這三個要素的權(quán)重總和來確定匹配路段,依據(jù)道路的拓撲關(guān)系、交通規(guī)則管制,在權(quán)重總和最大及次大的待匹配路段中選取最佳匹配路段。若仍無法從權(quán)重最大和次大的候選匹配路段中選取最優(yōu)匹配路段,則將此定位點的相關(guān)信息記下,繼續(xù)后續(xù)定位點的匹配,待后續(xù)定位點匹配完成后,利用最短路徑算法來確定此定位點的匹配路段,再通過垂直投影法估計GPS定位點在此路段上的匹配位置。最后,在MATLAB平臺上進行仿真實驗,結(jié)果證明該算法是正確有效的。與傳統(tǒng)的基于權(quán)重的地圖匹配算法相比,改進后的基于權(quán)重的地圖匹配算法通過網(wǎng)格劃分和構(gòu)建誤差區(qū)域降低了在選取候選匹配路段時的時空復雜度。
[Abstract]:Map matching is a correction method widely used in navigation system location, which is based on software technology. Through the algorithm model, the vehicle track obtained by the GPS terminal device is associated with the topological road in the real map. Because map matching is very practical in traffic system, many scholars have spent a lot of time studying it. Many algorithms related to map matching are put forward, which have their own advantages and disadvantages. Whether the positioning error of navigation system can be reduced directly reflects the performance of map matching algorithm. However, the real-time and robustness of the algorithm can not be ignored. Because most of the existing map matching algorithms only consider the algorithm itself, the practicability of the algorithm is relatively weak. So we should consider merging other effective elements into the algorithm to improve the practicability of the algorithm. In short, in the design of map matching algorithm, compare the advantages and disadvantages of many algorithms. Finally, a map matching algorithm with high real-time, robustness and matching accuracy is realized by combining these algorithms effectively. This paper analyzes the factors that affect the matching accuracy of map matching algorithm, and carries on a series of research and summary to the existing map matching algorithm. On this basis, we propose a road network topology characteristics as the premise. Use the latitude and longitude of the current vehicle position. The basic idea of the algorithm proposed in this paper is to mesh the electronic map to determine the grid number of the GPS location point. Then by constructing the error region to reduce the search range of the matching, the number of candidate matching sections is reduced. Finally, a matching model is constructed to calculate the matching degree between GPS positioning points and candidate matching sections. The weight model is based on the calculation of the shortest distance between the GPS location point and the candidate matching section and the angle between the driving direction of the GPS location point and the candidate matching section. The relative position relationship between the location point and the candidate matching section is determined by the sum of the weights of the three elements. According to the topological relationship of the road, the traffic rules control. The best matching section is selected in the section to be matched with the largest and the second largest weights. If the optimal matching section can not be selected from the candidate matching section with the largest and the second largest weight, the relevant information of this location point is noted down. Continue the matching of the following location points, and then use the shortest path algorithm to determine the matching section of the location point after the completion of the subsequent location point matching. Then the matching position of GPS positioning point on this section is estimated by vertical projection method. Finally, the simulation experiment is carried out on the MATLAB platform. The results show that the algorithm is correct and effective, compared with the traditional weighted map matching algorithm. The improved weighted map matching algorithm reduces the space-time complexity of selecting candidate matching sections by mesh generation and error region construction.
【學位授予單位】：武漢理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：U495;P228.4

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