本文選題：智能交通 + 車牌識別數(shù)據(jù)��； 參考：《青島科技大學(xué)》2017年碩士論文

【摘要】：隨著城市規(guī)模的擴(kuò)大和經(jīng)濟(jì)的飛速發(fā)展,道路交通負(fù)荷和交通擁擠現(xiàn)象日益嚴(yán)重,交通供需矛盾日益突出。針對出現(xiàn)的問題,智能交通系統(tǒng)應(yīng)運(yùn)而生,它可以提高交通運(yùn)輸效率、改善交通擁擠狀況、保障車輛安全運(yùn)行,為交通運(yùn)輸提供更有效的管理手段,為民眾提供更好的服務(wù)。近幾年,中國許多城市開始采用基于車牌識別的交通信息采集技術(shù)來輔助進(jìn)行道路交通管理。該技術(shù)能夠得到城市道路行駛車輛的實(shí)時(shí)監(jiān)測數(shù)據(jù),該數(shù)據(jù)具有持續(xù)生成且數(shù)據(jù)量大、時(shí)間空間相關(guān)等特性。目前基于車牌識別數(shù)據(jù)的智能交通相關(guān)的研究較少,高成本的車牌識別系統(tǒng)僅能實(shí)現(xiàn)交通監(jiān)控、流量檢測等較為簡單的功能,使其性價(jià)比較低,因此如何充分利用車牌識別數(shù)進(jìn)行智能交通的相關(guān)研究是當(dāng)前的研究熱點(diǎn)。本文首先研究了當(dāng)前交通信息采集技術(shù)、車牌識別系統(tǒng)及其采集的數(shù)據(jù)特點(diǎn)。針對可能出現(xiàn)的錯(cuò)誤數(shù)據(jù)及缺失數(shù)據(jù),給出了相應(yīng)的識別與修復(fù)方法,在數(shù)據(jù)處理后得出旅行時(shí)間的估計(jì)值。第二,提出一種基于車牌識別數(shù)據(jù)的城市道路交通狀態(tài)判別方法,該方法基于模糊理論實(shí)現(xiàn)交通狀態(tài)判別,并利用青島市某路段的車牌識別數(shù)據(jù)對該方法進(jìn)行實(shí)際檢驗(yàn),結(jié)果證明該方法確實(shí)有效。第三,研究了基于車牌識別數(shù)據(jù)的旅行時(shí)間可靠性分析,發(fā)現(xiàn)城市道路旅行時(shí)間符合對數(shù)正態(tài)分布,對對數(shù)正態(tài)分布函數(shù)的性質(zhì)及旅行時(shí)間可靠性的相關(guān)指標(biāo)進(jìn)行了分析。本文選取緩沖指數(shù)作為旅行時(shí)間可靠性指標(biāo),確定了基于車牌識別數(shù)據(jù)進(jìn)行旅行時(shí)間可靠性分析的一般流程,通過某路段實(shí)際數(shù)據(jù)進(jìn)行仿真分析證明了方法的有效性。
[Abstract]:With the expansion of city scale and the rapid development of economy, the traffic load and traffic congestion are becoming more and more serious, and the contradiction of traffic supply and demand is becoming more and more prominent. In view of the problems, Intelligent Transportation system (its) emerges as the times require. It can improve the efficiency of transportation, improve traffic congestion, ensure the safe operation of vehicles, provide more effective management means for transportation and provide better services for the public. In recent years, many cities in China began to use license plate recognition based traffic information collection technology to assist in road traffic management. This technique can obtain real-time monitoring data of urban road vehicles, which has the characteristics of continuous generation, large amount of data, time and space correlation, and so on. At present, there are few researches on intelligent transportation based on license plate recognition data. The high cost license plate recognition system can only realize simple functions such as traffic monitoring, flow detection and so on, which makes its performance-price ratio lower. Therefore, how to make full use of license plate recognition number to carry on the related research of intelligent transportation is the current research hot spot. In this paper, the current traffic information acquisition technology, license plate recognition system and its data collection characteristics are studied. According to the error data and missing data, the corresponding recognition and repair methods are given, and the estimated travel time is obtained after data processing. Secondly, a traffic state discrimination method based on license plate recognition data is proposed. The method is based on fuzzy theory to realize traffic state discrimination, and the method is tested by the license plate recognition data of a section of Qingdao. The results show that the method is effective. Thirdly, the travel time reliability analysis based on license plate recognition data is studied. It is found that urban road travel time conforms to the lognormal distribution. The properties of the logarithmic normal distribution function and the related indexes of travel time reliability are analyzed. In this paper, the buffer index is selected as the travel time reliability index, and the general flow of travel time reliability analysis based on license plate recognition data is determined.
【學(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U491;TP391.41

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