發(fā)布時間：2018-11-24 18:54

【摘要】：隨著城市規(guī)模的極速擴(kuò)大,城市中的交通資源已經(jīng)不能趕上城市的擴(kuò)張速度。由于交通資源的緊張,導(dǎo)致了一系列社會問題：交通擁堵,交通事故頻發(fā),出行時間冗長等。隨著近兩年物聯(lián)網(wǎng)、車聯(lián)網(wǎng)、車路協(xié)同和互聯(lián)網(wǎng)大數(shù)據(jù)的蓬勃發(fā)展,融合各種領(lǐng)域領(lǐng)先技術(shù)的智能交通誘導(dǎo)系統(tǒng)應(yīng)運(yùn)而生。但是目前的交通誘導(dǎo)服務(wù)平臺存在著以下的問題：不能承載海量的用戶數(shù),開發(fā)和實驗周期非常長,大數(shù)據(jù)的處理能力不能滿足要求。 為此,本文在調(diào)研了各個領(lǐng)域的研究前沿后,針對上述問題提出了一套針對性的解決方案。PHP是當(dāng)今開發(fā)效率最高的語言,因此通過PHP開發(fā)誘導(dǎo)服務(wù)平臺有得天獨厚的優(yōu)勢。為了保證平臺能夠支撐海量的服務(wù)請求,本文提出了采用分布式的系統(tǒng)架構(gòu),使得系統(tǒng)能夠平滑地實現(xiàn)橫向擴(kuò)容,動態(tài)適配服務(wù)資源。由于PHP自身語言性能存在瓶頸,因此采用核心算法C擴(kuò)展化和HHVM化來保證系統(tǒng)的性能不受桎梏。 同時,本文提出了新型的異構(gòu)感知節(jié)點部署算法,能夠很大程度上提高網(wǎng)絡(luò)節(jié)點的部署效率。通過無縫融合RSSI、 GPS、 INS慣導(dǎo)系統(tǒng),提出了高速道路下的多模融合差分融合定位算法。通過浮動車采集路網(wǎng)的OD矩陣參數(shù),對傳統(tǒng)的Dijkstra算法進(jìn)行優(yōu)化,提出了一種高效的動態(tài)誘導(dǎo)算法。最后,針對上述理論分析和研究,在開放的私有云主機(jī)上實現(xiàn)算法并部署了交通誘導(dǎo)服務(wù)平臺的演示系統(tǒng),并對一些關(guān)鍵功能進(jìn)行了測試和分析,符合預(yù)期。
[Abstract]:With the rapid expansion of the city, the traffic resources in the city can not catch up with the expansion of the city. The shortage of traffic resources leads to a series of social problems: traffic congestion, frequent traffic accidents, long travel time and so on. With the rapid development of Internet of things, vehicle-road coordination and Internet big data, intelligent traffic guidance system (its), which integrates leading technologies in various fields, has emerged as the times require. However, the current traffic guidance service platform has the following problems: can not carry a large number of users, development and experimental period is very long, big data's processing capacity can not meet the requirements. Therefore, after investigating the research frontier in various fields, this paper puts forward a set of targeted solutions to the above problems. PHP is the language with the highest development efficiency nowadays, so it is advantageous to develop induction service platform through PHP. In order to ensure that the platform can support a large number of service requests, this paper proposes a distributed system architecture, which enables the system to smoothly achieve horizontal expansion, dynamic adaptation of service resources. Because of the bottleneck of PHP's own language performance, the core algorithms C extension and HHVM are adopted to ensure that the system performance is not shackled. At the same time, this paper proposes a new heterogeneous aware node deployment algorithm, which can greatly improve the deployment efficiency of network nodes. Through seamless fusion of RSSI, GPS, INS inertial navigation system, a multi-mode fusion differential fusion localization algorithm for high-speed road is proposed. By collecting the OD matrix parameters of the road network by floating vehicle, the traditional Dijkstra algorithm is optimized, and an efficient dynamic induction algorithm is proposed. Finally, in view of the above theoretical analysis and research, the algorithm is implemented on the open private cloud host and the demonstration system of the traffic guidance service platform is deployed, and some key functions are tested and analyzed to meet the expectations.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U495

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 楊東凱,吳今培,張其善;智能交通系統(tǒng)及其信息化模型[J];北京航空航天大學(xué)學(xué)報;2000年03期

2 穆利娜;李發(fā)紅;;基于GIS的城市智能交通誘導(dǎo)系統(tǒng)分析[J];測繪技術(shù)裝備;2007年04期

3 李玉芝;方源敏;;城市公交查詢系統(tǒng)的設(shè)計與實現(xiàn)[J];地礦測繪;2006年01期

4 楊蔭凱;智能交通系統(tǒng)(ITS)概述及我國的發(fā)展對策選擇[J];地理科學(xué)進(jìn)展;1999年03期

5 汪宏f,熊飛,史鐵林;高速高精度的機(jī)器視覺定位的算法[J];光電工程;2005年09期

6 馬燕;袁蔚林;陳秀萬;許玉斌;孫華波;;基于WiFi與GPS組合定位算法的無縫定位方法研究[J];地理與地理信息科學(xué);2013年03期

7 陳錫劍;程良倫;;基于RSSI的功率匹配定位算法的研究與實現(xiàn)[J];傳感技術(shù)學(xué)報;2013年05期

8 吳曉平;陸炳斌;沈浩;;基于RSSI定位模型的非視距關(guān)系識別方法[J];傳感技術(shù)學(xué)報;2013年11期

9 李論;丁恩杰;郝麗娜;張雷;;一種改進(jìn)的煤礦井下指紋定位匹配算法[J];傳感技術(shù)學(xué)報;2014年03期

10 劉傅斌;;交通信息化與大數(shù)據(jù)時代的契合[J];科技創(chuàng)新與應(yīng)用;2014年32期

，

本文編號：2354663