本文選題：微觀(guān)交通仿真 + 參數(shù)校正　； 參考：《吉林大學(xué)》2015年碩士論文

【摘要】：隨著城市的快速發(fā)展，居民私家車(chē)保有量逐年遞增，交通擁堵問(wèn)題已經(jīng)在很多城市引起了有關(guān)部門(mén)的極大關(guān)注。微觀(guān)交通仿真軟件是評(píng)估交通解決方案的有力工具，因此軟件模型的精確性就顯得至關(guān)重要。目前，我國(guó)大多數(shù)研究機(jī)構(gòu)所使用的交通仿真軟件都從國(guó)外引進(jìn)，因此依據(jù)我國(guó)實(shí)際交通運(yùn)轉(zhuǎn)狀況對(duì)軟件模型參數(shù)進(jìn)行校正是開(kāi)展其余工作的前提和基礎(chǔ)。以往的參數(shù)校正算法大多采用遺傳算法，但是遺傳算法在迭代過(guò)程中會(huì)耗費(fèi)大量的時(shí)間，同時(shí)目前大多數(shù)校正的方法都是獨(dú)立的程序，并未達(dá)成參數(shù)校正的自動(dòng)化，為了解決上述問(wèn)題，本文建立了基于改進(jìn)方法的VISSIM參數(shù)自動(dòng)校正體系。在研究過(guò)程中，主要實(shí)現(xiàn)了以下幾個(gè)方面的工作： 首先，，經(jīng)過(guò)對(duì)大量文獻(xiàn)的閱讀和整理，歸納出目前對(duì)于參數(shù)校正工作的研究正沿著兩條主線(xiàn)展開(kāi)，而本文的研究重點(diǎn)也放在對(duì)于模型校正算法的研究上。本文以VISSIM仿真軟件為例，對(duì)軟件的核心模型——跟馳模型和換道模型的重要參數(shù)進(jìn)行了詳細(xì)地說(shuō)明，然后對(duì)參數(shù)校正過(guò)程中評(píng)價(jià)指標(biāo)的選取和待校正參數(shù)的選取方法做了具體地介紹。 其次，本文以遺傳算法為參數(shù)校正方法，利用訓(xùn)練好的廣義回歸神經(jīng)網(wǎng)絡(luò)模型預(yù)測(cè)仿真軟件VISSIM的輸出結(jié)果，這樣就避免了在遺傳算法迭代過(guò)程中需要反復(fù)運(yùn)轉(zhuǎn)仿真軟件造成的時(shí)間浪費(fèi)。這部分也是論文的核心之一。之后本文以北京市中關(guān)村一街為實(shí)例，對(duì)上述參數(shù)校正方法進(jìn)行了實(shí)例驗(yàn)證，結(jié)果證明，該方法能夠有效提高參數(shù)校正的效率，并且符合對(duì)模型精度的要求。 接著，文章建立了交通仿真軟件自動(dòng)校正體系，達(dá)成了參數(shù)校正的流程化和自動(dòng)化，用戶(hù)能夠經(jīng)過(guò)簡(jiǎn)單的圖形界面達(dá)成對(duì)參數(shù)校正流程的控制，同時(shí)能夠獲得更加直觀(guān)的校正前后參數(shù)和評(píng)價(jià)指標(biāo)的對(duì)照狀況。 最終，文章對(duì)上述建立的自動(dòng)校正體系進(jìn)行了實(shí)例的驗(yàn)證，驗(yàn)證的區(qū)域是江蘇省無(wú)錫市新區(qū)的主干道——菱湖大道從高浪路到震澤路路段，以平均行程時(shí)間為評(píng)價(jià)指標(biāo)，以浮動(dòng)車(chē)跟車(chē)和實(shí)地調(diào)查的方式對(duì)交通流數(shù)據(jù)進(jìn)行了采集，并在VISSIM平臺(tái)上建立了仿真模型。運(yùn)轉(zhuǎn)結(jié)果表明，用戶(hù)能夠經(jīng)過(guò)該體系達(dá)成對(duì)模型參數(shù)校正的空子，并且模型校正的結(jié)果在可接受的范圍內(nèi)。
[Abstract]:With the rapid development of cities, the number of private cars is increasing year by year. Traffic congestion has aroused great concern of relevant departments in many cities. Microscopic traffic simulation software is a powerful tool for evaluating traffic solutions, so the accuracy of the software model is very important. At present, the traffic simulation software used by most research institutions in our country is imported from abroad, so it is the premise and foundation of the other work to correct the parameters of the software model according to the actual traffic operation in our country. In the past, most of the parameter correction algorithms used genetic algorithm, but the genetic algorithm in the iterative process will cost a lot of time, and most of the current correction methods are independent procedures, did not achieve the automation of parameter correction. In order to solve the above problems, an automatic correction system of VISSIM parameters based on the improved method is established. In the course of the research, the following aspects of the work are realized: First of all, through reading and sorting out a large number of documents, we conclude that the research of parameter correction is being carried out along two main lines, and the research emphasis of this paper is also on the research of model correction algorithm. Taking the VISSIM simulation software as an example, this paper gives a detailed description of the important parameters of the core model of the software, that is, the car-following model and the changing channel model. Then the selection of the evaluation index and the method of selecting the parameters to be corrected in the process of parameter correction are introduced in detail. Secondly, using the genetic algorithm as the parameter correction method, the trained generalized regression neural network model is used to predict the output of the simulation software VISSIM. In this way, the time waste caused by running simulation software repeatedly in the iterative process of genetic algorithm is avoided. This part is also one of the core of the paper. Then this paper takes Zhongguancun first Street in Beijing as an example to verify the above parameter correction method. The results show that the method can effectively improve the efficiency of parameter correction and meet the requirements of model accuracy. Then, the automatic correction system of traffic simulation software is established, and the process and automation of parameter correction are achieved. The user can control the process of parameter correction through a simple graphical interface. At the same time, the comparison of parameters and evaluation indexes before and after correction can be obtained more intuitively. Finally, the paper verifies the automatic correction system, which is the main road of Wuxi City, Jiangsu Province, from Gaolang Road to Zhenze Road, and takes the average travel time as the evaluation index. The traffic flow data were collected by floating vehicle following vehicle and field investigation, and the simulation model was established on VISSIM platform. The operation results show that the user can achieve the model parameter correction through the system, and the model correction results are acceptable.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U495;TP391.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 毛保華,楊肇夏,陳海波;道路交通仿真技術(shù)與系統(tǒng)研究[J];北方交通大學(xué)學(xué)報(bào);2002年05期

2 叢明煜,王麗萍;現(xiàn)代啟發(fā)式算法理論研究[J];高技術(shù)通訊;2003年05期

3 許倫輝;倪艷明;羅強(qiáng);黃艷國(guó);;基于最小安全距離的車(chē)輛換道模型研究[J];廣西師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2011年04期

4 成衛(wèi);袁滿(mǎn)榮;陳輝;;基于Q-paramics的微觀(guān)交通仿真模型參數(shù)校正[J];系統(tǒng)工程;2013年02期

5 葛繼科;邱玉輝;吳春明;蒲國(guó)林;;遺傳算法研究綜述[J];計(jì)算機(jī)應(yīng)用研究;2008年10期

6 孫劍,楊曉光;微觀(guān)交通仿真模型系統(tǒng)參數(shù)校正研究——以VISSIM的應(yīng)用為例[J];交通與計(jì)算機(jī);2004年03期

7 胡明偉,郭秀芝;用微觀(guān)交通仿真軟件實(shí)現(xiàn)ITS模擬的比較研究[J];交通與計(jì)算機(jī);2004年04期

8 臧志剛;陸鋒;李海峰;崔海燕;;7種微觀(guān)交通仿真系統(tǒng)的性能評(píng)價(jià)與比較研究[J];交通與計(jì)算機(jī);2007年01期

9 張起靈;;北京治理交通擁堵的歷程回顧[J];汽車(chē)與安全;2013年09期

本文編號(hào)：1803459