本文選題：汽車運行工況 + 采樣時間�。� 參考：《吉林大學(xué)》2016年碩士論文

【摘要】：由于缺乏相應(yīng)的理論支持,一直以來,在進行汽車運行工況試驗時,試驗人員很難確定何時終止采樣。為保證試驗數(shù)據(jù)的完備性,試驗人員往往會延長采樣時間,從而導(dǎo)致大量時間被浪費,延長了汽車開發(fā)周期。為解決這一問題,本文利用統(tǒng)計推斷方法,從城市道路每天每車行駛次數(shù)分布和區(qū)域每天每車每平方公里行駛次數(shù)分布兩個角度,提出了采樣時間確定方法。首先,如果要在道路尺度上進行分析,就必須有對應(yīng)城市的電子地圖。本文提出一種面向交通網(wǎng)絡(luò)分析的道路電子地圖生成方法。該方法利用覆蓋城市區(qū)域的網(wǎng)格與汽車軌跡線的交點存儲軌跡的位置信息,大大減小了儲存空間和道路生成時的處理時間。同一網(wǎng)格線下,同一道路的所有軌跡線與網(wǎng)格線的交點的平均值就可以代表道路中心線與網(wǎng)格的交點。按照汽車的行駛順序?qū)⒔稽c依次連接就得到了電子地圖。汽車運行工況試驗的關(guān)鍵在于采樣獲得的城市道路行駛次數(shù)分布要與真實的城市道路流量分布相一致,所以還需要一種快速的地圖匹配算法。本文提出一種基于網(wǎng)格的道路匹配算法,相比較于其他方法,此方法更關(guān)注找到匹配道路而不是匹配在道路的哪個位置。最終本文得到了汽車在每條道路上的行駛次數(shù)和城市交通網(wǎng)絡(luò),進而獲得道路流量的抽樣分布。大量的理論和實證研究發(fā)現(xiàn),城市交通網(wǎng)絡(luò)是復(fù)雜網(wǎng)絡(luò)。道路的流量分布具有冪律分布特性,也就是說如果采樣得到的城市道路行駛次數(shù)分布能夠真實的反映道路流量分布冪律特性,采樣就可以終止。但是,在對城市道路流量分布進行估計之前,需要保證每條道路行駛次數(shù)估計的準(zhǔn)確性。本文采用中心極限定理對每條道路行駛次數(shù)的準(zhǔn)確性進行量化估計,當(dāng)精度滿足試驗之前確定的閾值時,就可以進行城市道路行駛次數(shù)分布的參數(shù)估計。由于在雙對數(shù)坐標(biāo)下,冪律分布為一條直線,所以文中選用普通最小二乘法來估計分布參數(shù)。然而在實際應(yīng)用中發(fā)現(xiàn),分布參數(shù)的置信區(qū)間隨時間波動太大,難以用于終止時間的判斷,所以最終以分布參數(shù)的穩(wěn)定性作為判斷采樣終止的依據(jù)。通過兩次模擬采樣,得到了長春的合理采樣時間為50天左右。由于在道路尺度上需要分析的狀態(tài)多,分析步驟繁瑣,需要進行電子地圖生成和道路匹配等原因,造成了估計的采樣時間偏長。為解決上述問題,本文還提出一種在區(qū)域尺度上確定采樣時間的方法。進行區(qū)域尺度分析的第一步就是考慮汽車運行工況試驗分析在區(qū)域尺度的可行性。在文中,通過K核算法和最優(yōu)分割理論獲得了長春的道路K核等級。對同一等級下道路的速度加速度聯(lián)合概率分布(VA分布)進行統(tǒng)計分析發(fā)現(xiàn),它們之間具有較高的相似性,且同一等級的道路經(jīng)常聚集在一個區(qū)域。這一現(xiàn)象表明,同一K核等級下的道路可以放在一起分析。也就是說,在區(qū)域尺度上進行汽車運行工況采樣時間的分析是合理的�；陂L春100臺出租車一個月的試驗數(shù)據(jù)和北京2340臺出租車7天的試驗數(shù)據(jù),本文分別得到了長春和北京的區(qū)域行駛次數(shù)分布。這兩個分布將會作為判斷采樣分布質(zhì)量的標(biāo)準(zhǔn)分布。采用K-S檢驗,發(fā)現(xiàn)Nakagami分布和指數(shù)分布可以對城市的區(qū)域行駛次數(shù)分布進行描述。接著,通過統(tǒng)計推斷理論估計出了長春和北京采樣時間,其中對于Nakagami分布和指數(shù)分布的參數(shù)估計使用的是最大似然估計法。經(jīng)計算,長春需要26天就能完成采樣,北京則需要95天左右。對區(qū)域尺度的采樣時間確定方法進行分析后發(fā)現(xiàn),影響采樣精度(采樣終止條件)的主要因素為每個采樣區(qū)域行駛次數(shù)的準(zhǔn)確性。通過分析試驗數(shù)據(jù)發(fā)現(xiàn),采樣得到的城市區(qū)域行駛次數(shù)的變異系數(shù)和區(qū)域行駛次數(shù)抽樣分布與真實分布的相似性度量ab?具有線性關(guān)系。本文通過公式推導(dǎo),從理論上證明了這一線性關(guān)系。這說明在進行汽車運行工況采樣的時候,可以根據(jù)計算得到的城市區(qū)域行駛次數(shù)的變異系數(shù)判斷是否終止采樣。
[Abstract]:Because of the lack of theoretical support, it is difficult for the experimenters to determine when to terminate the sampling during the test of the vehicle operating conditions. In order to ensure the completeness of the test data, the experimenters often extend the sampling time, resulting in a large amount of time wasted and the extension of the vehicle development cycle. This paper uses this problem to solve this problem. The method of statistical inference, from the two angles of the distribution of each car per vehicle per day and the distribution of each square kilometer per square kilometer per day in the city, proposed the method of determining the sampling time. First, if we want to analyze the road scale, we must have the corresponding City Electronic Map. This paper presents a traffic network analysis. The method of generating the road map. This method uses the intersection of the grid covering the city area and the car track line to store the location information of the track, which greatly reduces the storage space and the processing time of the road generation. Under the same grid, the average value of the intersection of all the track lines and the grid lines on the same road can represent the center of the road. The intersection of line and grid. The key of the vehicle running test is that the distribution of urban road travel times is in accordance with the true urban road flow distribution, so a fast map matching algorithm is needed. Compared with other methods, the road matching algorithm in grid is more concerned about finding the way to match the road instead of matching the road. Finally, this paper obtains the number of cars on each road and the urban traffic network, and then obtains the sampling distribution of the road traffic. A large number of theoretical and empirical studies find that the city is a city. Traffic network is a complex network. The flow distribution of road has power law distribution, that is to say, if the distribution of urban road travel times can truly reflect the power law characteristic of road flow distribution, sampling can be terminated. But before estimating the urban road flow distribution, every road must be guaranteed. The accuracy of the number of times is quantified by the central limit theorem. When the precision meets the threshold determined before the test, the parameter estimation of the number of urban road travel times can be estimated. Because the power law distribution is a straight line in the double logarithmic coordinates, the article selects the general. In the practical application, it is found that the confidence interval of the distribution parameters fluctuates too much with time, and it is difficult to use the judgment of the termination time. Therefore, the stability of the distribution parameters is used as the basis for judging the termination of the sampling. The reasonable sampling time of Changchun is 50 days by the two simulated sampling. In order to solve the above problems, a method to determine the sampling time on the regional scale is also proposed. The first step of the regional scale analysis is to take the examination of the regional scale. The feasibility of vehicle operation test analysis at regional scale is considered. In this paper, the road K nuclear grade in Changchun is obtained by K kernel algorithm and optimal segmentation theory. The statistical analysis of the joint probability distribution of velocity and acceleration (VA distribution) on the same grade road shows that they have high similarity and the same grade of road between them. It is often gathered in one area. This phenomenon indicates that the road under the same K nuclear grade can be analyzed together. That is, it is reasonable to analyze the sampling time of the vehicle operating conditions at the regional scale. Based on the one month test data of 100 taxis in Changchun and the test data of 2340 taxis in Beijing for 7 days, this paper respectively The distribution of regional travel times in Changchun and Beijing will be obtained. These two distributions will be used as the standard distribution of sampling distribution quality. Using K-S test, it is found that Nakagami distribution and exponential distribution can describe the distribution of regional travel times in cities. Then, the sampling time of Changchun and Beijing is estimated by statistical inference theory. The maximum likelihood estimation method is used for the parameter estimation of the Nakagami distribution and the exponential distribution. It is calculated that Changchun takes 26 days to complete the sampling and Beijing takes about 95 days. After analyzing the sampling time determination method of the regional scale, it is found that the main factors affecting the sampling accuracy (sampling termination condition) are each sampling area. Through the analysis of the test data, it is found that the variation coefficient of the number of urban travel times and the sampling distribution of the regional travel times are linear with the similarity measure of the true distribution of the urban area. This paper has proved this linear relationship theoretically by derivation of the formula. This shows that the running condition of the car is carried out in the operation of the car. At the time of sampling, we can decide whether to stop sampling according to the coefficient of variation of the number of times traveled in the urban area.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：U467

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