本文選題：視頻檢測 + 行程時(shí)間��； 參考：《山東大學(xué)》2015年碩士論文

【摘要】：隨著城市交通的不斷發(fā)展,智能交通管理系統(tǒng)在城市交通管理中發(fā)揮了越來越重要的作用,而其中城市道路卡口監(jiān)控系統(tǒng)的廣泛應(yīng)用又推動(dòng)了智能交通的快速發(fā)展�？ǹ谙到y(tǒng)具有目標(biāo)車輛捕捉、車牌識別、斷面車流統(tǒng)計(jì)、違法抓拍等功能。卡口系統(tǒng)已經(jīng)成為智能交通管理系統(tǒng)中的重要組成部分,城市和城市交通管理者也越來越重視通過卡口系統(tǒng)進(jìn)行數(shù)據(jù)的深度挖掘與利用。交通狀態(tài)是交通信息服務(wù)系統(tǒng)的基礎(chǔ),城市道路實(shí)時(shí)交通信息是實(shí)現(xiàn)交通管理及控制、動(dòng)態(tài)誘導(dǎo)、以及改善道路通行條件的基礎(chǔ),對城市規(guī)劃、公交調(diào)度、市民出行等均具有重要參考價(jià)值�，F(xiàn)有交通狀態(tài)估計(jì)大都是基于數(shù)理統(tǒng)計(jì)或者模式識別等方法對交通狀態(tài)進(jìn)行劃分,但這些劃分方法都是主觀的,相關(guān)研究缺乏主觀與客觀的結(jié)合。本文以道路實(shí)際行程時(shí)間信息為基礎(chǔ)數(shù)據(jù),結(jié)合駕駛員期望建立交通狀態(tài)評價(jià)方法,實(shí)現(xiàn)了主客觀的結(jié)合。整個(gè)論文包括以下幾個(gè)部分。首先,卡口系統(tǒng)作為智能交通管理系統(tǒng)的重要部分,已經(jīng)廣泛的應(yīng)用于我國大部分城市。通過卡口系統(tǒng)的車牌識別功能可以獲得同一輛車通過不同檢測點(diǎn)位的時(shí)間信息,由此對車牌號碼進(jìn)行匹配計(jì)算得到車輛的路段行程時(shí)間。由于檢測設(shè)備自身的工作原理以及交通流的自主行為,造成采集的數(shù)據(jù)出現(xiàn)錯(cuò)誤,主要表現(xiàn)為數(shù)據(jù)丟失和數(shù)據(jù)異常。本文利用卡口系統(tǒng)采集的文本信息創(chuàng)建數(shù)據(jù)信息庫,針對不同情況下的數(shù)據(jù)缺失進(jìn)行合理的修復(fù),采用類似于t檢定或者z檢定的中位值偏差法對異常數(shù)據(jù)進(jìn)行處理,經(jīng)過處理后的數(shù)據(jù)計(jì)算得到車輛的路段行程時(shí)間樣本集。準(zhǔn)確的行程時(shí)間樣本是交通狀態(tài)估計(jì)的基本前提,交通狀態(tài)的合理估計(jì)還需要建立完善的評價(jià)指標(biāo)。基于行程時(shí)間的指標(biāo)很容易被交通參與者理解,行程時(shí)間可以從不同的時(shí)間、空間維度上按不同要求描述交通狀況；行程時(shí)間指標(biāo)既能恰當(dāng)?shù)拿枋鎏囟ǖ攸c(diǎn)交通擁擠狀況,也能描述整個(gè)道路交通擁擠狀況。現(xiàn)有交通狀態(tài)指標(biāo)均假設(shè)不同道路等級的交通狀態(tài)具有一致性,當(dāng)單個(gè)路段或單個(gè)車輛的交通狀態(tài)指標(biāo)相同時(shí)則認(rèn)為擁堵程度也相同,但是從管理者和駕駛員的角度講,在不同等級道路的路段上,交通狀態(tài)相同時(shí)管理者和駕駛員的感受是不相同的,例如在快速路和干道上速度同樣降低20%,管理者和駕駛員認(rèn)為在快速路更為擁堵,主要是因?yàn)槌鲂姓咴诳焖俾飞掀谕慕^對行駛速度和相對行駛速度均比較高,所以不同路段或單個(gè)車輛計(jì)算交通狀態(tài)時(shí)需要考慮駕駛員的感受。本文對通過對駕駛員進(jìn)行期望速度調(diào)查,以路段行程時(shí)間為基礎(chǔ),結(jié)合駕駛員期望速度,制定了交通狀態(tài)評價(jià)指標(biāo)。最后,本文將將交通狀態(tài)分為暢通、輕度暢通、輕度擁堵、中度擁堵、嚴(yán)重?fù)矶挛鍌�(gè)等級,并編程實(shí)現(xiàn)交通狀態(tài)的顯示。
[Abstract]:With the continuous development of urban traffic, intelligent traffic management system (its) has played an increasingly important role in urban traffic management, and the wide application of urban road bayonet monitoring system has promoted the rapid development of intelligent transportation. The bayonet system has the functions of target vehicle capture, license plate recognition, cross-section traffic flow statistics, illegal capture and so on. The bayonet system has become an important part of the intelligent traffic management system, and city traffic managers pay more and more attention to the depth mining and utilization of data through the bayonet system. The traffic state is the foundation of the traffic information service system, and the real-time traffic information of the city road is the basis of realizing the traffic management and control, the dynamic guidance, and the improvement of the road traffic conditions. The citizen travel and so on all has the important reference value. Most of the existing traffic state estimation methods are based on mathematical statistics or pattern recognition, but these methods are subjective and lack of the combination of subjective and objective. Based on the information of road travel time and the expectation of drivers, this paper establishes a method of traffic condition evaluation, and realizes the combination of subjective and objective. The whole paper includes the following parts. Firstly, as an important part of intelligent traffic management system, bayonet system has been widely used in most cities of our country. Through the license plate recognition function of the bayonet system, the time information of the same vehicle passing through different detection points can be obtained, and then the vehicle section travel time can be calculated by matching the license plate number. Because of the working principle of the detection equipment and the independent behavior of the traffic flow, there are errors in the collected data, which are mainly reflected in the data loss and data anomalies. In this paper, the text information collected by the bayonet system is used to create the data information database, and the data missing in different cases is repaired reasonably. The method of midpoint deviation similar to t test or z test is used to deal with the abnormal data. The processed data are calculated to get the sample set of the road travel time of the vehicle. Accurate travel time sample is the basic premise of traffic state estimation. The index based on travel time is easy to be understood by traffic participants. Travel time can be described according to different requirements in different time and space dimensions. It can also describe the whole road traffic congestion. The existing traffic state indicators all assume that the traffic state of different road grades is consistent. When the traffic condition index of a single road section or a single vehicle is the same, the traffic congestion degree is the same, but from the perspective of managers and drivers, On different levels of roads, managers and drivers feel differently when the traffic is in the same state. For example, on expressways and trunk roads, the speed is also reduced by 20 percent, and managers and drivers think that it is more congested on expressways. The main reason is that both the absolute speed and the relative speed expected by the traveler on the expressway are relatively high, so it is necessary to consider the driver's feeling when calculating the traffic state of different sections or individual vehicles. In this paper, through the investigation of the expected speed of the driver, based on the travel time of the road, combined with the expected speed of the driver, the evaluation index of the traffic condition is established. Finally, this paper will divide the traffic state into five grades: smooth, mild, moderate and severe congestion, and realize the display of traffic state by programming.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491;TP274

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