【摘要】：隨著橋梁跨度的不斷增大、車(chē)流量的不斷增加、車(chē)速的不斷提升以及重車(chē)及超重車(chē)的不斷出現(xiàn)等眾多因素,作用在橋梁上的隨機(jī)車(chē)流變得越來(lái)越復(fù)雜。由于大跨橋梁上的隨機(jī)車(chē)流荷載具有較強(qiáng)的隨機(jī)性,傳統(tǒng)的假定車(chē)間距及車(chē)速不變的研究方法具有較大的局限性,難以對(duì)隨機(jī)車(chē)流荷載的特性進(jìn)行準(zhǔn)確的分析。本文基于南京長(zhǎng)江二橋收費(fèi)站取得的隨機(jī)車(chē)流數(shù)據(jù)結(jié)合實(shí)測(cè)的車(chē)流數(shù)據(jù),統(tǒng)計(jì)了二橋各類車(chē)型的車(chē)重特征參數(shù),研究了大跨橋梁各個(gè)不同車(chē)道的在不同交通服務(wù)水平下的車(chē)型比例以及車(chē)輛到達(dá)率等特征參數(shù);基于元胞自動(dòng)機(jī)模型(CA模型)的基本思想,從交通控制理論的單車(chē)道元胞自動(dòng)機(jī)模型入手,并結(jié)合實(shí)測(cè)的各車(chē)道車(chē)型比例及斷面發(fā)車(chē)率等斷面發(fā)車(chē)數(shù)據(jù)以建立多車(chē)道隨機(jī)車(chē)流模型的數(shù)學(xué)模型,依托Matlab開(kāi)發(fā)了多車(chē)道隨機(jī)車(chē)流模擬程序,以對(duì)二橋的隨機(jī)車(chē)流進(jìn)行仿真模擬,并對(duì)隨機(jī)車(chē)流運(yùn)行過(guò)程中的車(chē)流特性進(jìn)行了研究。主要包括以下幾個(gè)方面的內(nèi)容：(1)研究車(chē)輛在橋梁上的行駛規(guī)律,包括加減速原則以及車(chē)輛在行駛過(guò)程中換道規(guī)律,確定車(chē)輛在需要換道時(shí)應(yīng)如何換道以及換道的概率。根據(jù)車(chē)流的運(yùn)行規(guī)則并基于CA模型思想建立大跨橋梁多車(chē)道隨機(jī)車(chē)流的數(shù)學(xué)模型。(2)基于建立的隨機(jī)車(chē)流的數(shù)學(xué)模型并依托Matlab軟件開(kāi)發(fā)大跨橋梁多車(chē)道隨機(jī)車(chē)流模擬程序,以對(duì)二橋的隨機(jī)車(chē)流進(jìn)行仿真模擬,利用Matlab的界面設(shè)計(jì)功能以及句柄圖形功能進(jìn)行模擬程序的輸出界面設(shè)計(jì),并實(shí)現(xiàn)隨機(jī)車(chē)流模擬的可視化。該程序的實(shí)現(xiàn)為得到隨機(jī)車(chē)流荷載數(shù)據(jù)提供了支持。(3)從南京長(zhǎng)江二橋收費(fèi)站以及通過(guò)對(duì)隨機(jī)車(chē)流進(jìn)行直接觀測(cè)統(tǒng)計(jì)獲取大量隨機(jī)車(chē)流交通特征參數(shù),包括車(chē)型比例參數(shù)、各個(gè)車(chē)道在不同交通服務(wù)水平下的斷面發(fā)車(chē)率以及不同車(chē)型車(chē)重?cái)?shù)據(jù)分布參數(shù)；對(duì)本文交通調(diào)查所取得的斷面發(fā)車(chē)率參數(shù)樣本的分布類型進(jìn)行了卡方擬合優(yōu)度檢驗(yàn),發(fā)現(xiàn)在不同交通服務(wù)水平下三個(gè)車(chē)道的斷面發(fā)車(chē)率基本服從泊松分布。(4)基于二橋的實(shí)測(cè)數(shù)據(jù)以及元胞自動(dòng)機(jī)模型理論對(duì)大跨橋梁的隨機(jī)車(chē)流進(jìn)行模擬,將模擬車(chē)流特征參數(shù)與實(shí)測(cè)車(chē)流數(shù)據(jù)進(jìn)行了對(duì)比分析,從而驗(yàn)證程序的準(zhǔn)確性及合理性；研究不同交通服務(wù)水平下車(chē)流的運(yùn)行特點(diǎn)；此外,進(jìn)一步對(duì)模擬隨機(jī)車(chē)流下的交通量、車(chē)速以及車(chē)間距進(jìn)行規(guī)律研究及特征分析,發(fā)現(xiàn)三種交通服務(wù)水平下的車(chē)間距都基本服從對(duì)數(shù)正態(tài)分布,擬合出了相應(yīng)的對(duì)數(shù)正態(tài)分布曲線,并通過(guò)K-S檢驗(yàn)對(duì)其進(jìn)行了驗(yàn)證。(5)通過(guò)對(duì)隨機(jī)車(chē)流的模擬可以得到每個(gè)時(shí)刻橋面上車(chē)輛的位置、對(duì)應(yīng)的車(chē)型、車(chē)重以及車(chē)速等參數(shù)。引入等效動(dòng)態(tài)車(chē)輛荷載方法(EDWL法),利用該方法將隨機(jī)車(chē)流位置轉(zhuǎn)換為了隨機(jī)車(chē)流荷載,簡(jiǎn)化車(chē)橋之間的相互作用,并生成橋梁部分?jǐn)嗝娴暮奢d時(shí)程曲線。
[Abstract]:With the increasing span of bridges, the increasing of traffic flow, the increasing speed of vehicles, and the emergence of heavy and overweight vehicles, the random traffic flow on the bridge becomes more and more complex. Because of the strong randomness of the random vehicle flow loads on long-span bridges, the traditional research methods which assume that the vehicle spacing and the speed are invariant have great limitations, so it is difficult to accurately analyze the characteristics of the random vehicle flow loads. Based on the random traffic flow data obtained from Nanjing No. 2 Changjiang River Bridge toll station and the measured traffic flow data, the characteristic parameters of vehicle weight of all kinds of vehicle types in the second bridge are calculated in this paper. Based on the cellular automata model (CA model), the paper studies the vehicle model proportion and vehicle arrival rate of different lanes of long span bridge under different traffic service levels. Starting with the single lane cellular automata model of traffic control theory and combining with the measured data of each lane model and section departure rate, the mathematical model of multi-lane stochastic vehicle flow model is established. Based on Matlab, a multi-lane stochastic vehicle flow simulation program is developed to simulate the random traffic flow of the second bridge, and the characteristics of the vehicle flow in the course of the random traffic flow are studied. The main contents are as follows: (1) study the driving law of vehicle on the bridge, including acceleration and deceleration principle and the law of vehicle changing in the course of driving, and determine how to change the road and the probability of changing the road when the vehicle needs to change the road. According to the running rules of vehicle flow and the idea of CA model, the mathematical model of multi-lane random vehicle flow of long-span bridge is established. (2) based on the established mathematical model of random traffic flow and relying on Matlab software, the simulation program of multi-lane random vehicle flow of long-span bridge is developed. The random traffic flow of the second bridge is simulated, the output interface of the simulation program is designed by using the interface design function of Matlab and the function of handle figure, and the visualization of the simulation of random traffic flow is realized. The implementation of the program provides support for obtaining random vehicle flow load data. (3) A large number of traffic characteristic parameters of random traffic flow, including model scale parameters, are obtained from Nanjing Changjiang River Bridge toll station and through direct observation and statistics of random traffic flow. Section departure rate and vehicle weight data distribution parameters of each lane under different traffic service levels. The distribution types of cross-section departure rate parameters obtained in this paper are tested by chi-square goodness of fit. It is found that the section departure rate of three lanes is distributed from Poisson under different traffic service levels. (4) based on the measured data of the second bridge and the cellular automata model theory, the random traffic flow of the long-span bridge is simulated. The characteristic parameters of simulated traffic flow are compared with the measured traffic flow data to verify the accuracy and reasonableness of the program; to study the running characteristics of the traffic flow under different traffic service levels; in addition, to further study the traffic volume under the simulation of random traffic flow, The law of vehicle speed and vehicle spacing is studied and the characteristics are analyzed. It is found that the distance between vehicles under the three traffic service levels is basically applied to the logarithmic normal distribution, and the corresponding logarithmic normal distribution curve is fitted out. It is verified by K-S test. (5) through the simulation of the random traffic flow, the position of the vehicle on the bridge deck at each moment, the corresponding vehicle type, the vehicle weight and the speed of the vehicle can be obtained. The equivalent dynamic vehicle load method (EDWL method) is introduced, by which the random vehicle flow position is transformed into the random vehicle flow load, which simplifies the interaction between the vehicle and the bridge, and generates the load time history curve of some sections of the bridge.
【學(xué)位授予單位】：南京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491;U441.2

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