【摘要】：交通流的波動(dòng)性和不確定性是交通控制復(fù)雜性的主要原因之一。這種波動(dòng)性不僅表現(xiàn)在不同時(shí)間上的交通流變化,也表現(xiàn)在不同空間上的交通流差異,本文主要研究面向交通控制的時(shí)段劃分與子區(qū)劃分,其中子區(qū)劃分部分又可根據(jù)控制區(qū)域的大小,分為用于干線協(xié)調(diào)控制的協(xié)調(diào)路口劃分和用于區(qū)域協(xié)調(diào)控制的子區(qū)劃分。 在時(shí)段劃分方面,分析了聚類數(shù)據(jù)的組成和間隔對時(shí)段劃分的影響,在對經(jīng)典的NJw譜聚類算法進(jìn)行改進(jìn)后,應(yīng)用在一個(gè)路口和多個(gè)路口的時(shí)段劃分中,并與K-means算法得到的結(jié)果進(jìn)行仿真對比.然后考慮使用多天的交通流數(shù)據(jù)后,對時(shí)段劃分流程進(jìn)行改進(jìn),使用主成分分析法對數(shù)據(jù)進(jìn)行降維處理后,使用Self-Tuning譜聚類算法進(jìn)行時(shí)段劃分,從聚類效果和仿真試驗(yàn)兩方面證明了該方法的有效性。接著考慮到交通流的時(shí)序特征,使用有序聚類對最佳周期數(shù)據(jù)進(jìn)行分析,效果優(yōu)于K-means算法。 在協(xié)調(diào)路口劃分方面,首先分析了Synchro軟件中用于描述路口關(guān)聯(lián)性的協(xié)調(diào)因子計(jì)算模型,然后用實(shí)例分析了Synchro軟件劃分協(xié)調(diào)路口的步驟和方法,仿真結(jié)果表明Synchro軟件無法直接得到最優(yōu)的劃分,而且協(xié)調(diào)路口的劃分對協(xié)調(diào)控制的效果具有顯著的影響。然后根據(jù)通過路口數(shù)最大的模型,建立了協(xié)調(diào)路口的劃分標(biāo)準(zhǔn),方法簡單有效。 在子區(qū)劃分方面,首先微觀仿真軟件VISSIM建立仿真環(huán)境,分別分析一個(gè)路口周期、綠信比、飽和度的變化對鄰近路口控制方案和控制效果的影響,以深入理解交叉口的關(guān)聯(lián)性。然后利用復(fù)雜網(wǎng)絡(luò)中的社團(tuán)劃分算法,進(jìn)行改進(jìn)后應(yīng)用在加權(quán)網(wǎng)絡(luò)中,得到大范圍交通網(wǎng)絡(luò)的子區(qū)劃分方法。
[Abstract]:The fluctuation and uncertainty of traffic flow is one of the main reasons for the complexity of traffic control. This fluctuation is not only reflected in the traffic flow variation in different time, but also in the traffic flow difference in different space. In this paper, the time division and sub-area division for traffic control are mainly studied. According to the size of the control area, the sub-area partition can be divided into coordinated intersection division for trunk line coordination control and sub-area division for area coordination control. In the aspect of time division, the influence of the composition and interval of clustering data on time division is analyzed. After improving the classical NJw spectral clustering algorithm, it is applied to the time division of one or more intersections. The simulation results are compared with the results obtained by K-means algorithm. Then, after considering the use of multi-day traffic flow data, the process of time division is improved. After dimensionality reduction of data is processed by principal component analysis, Self-Tuning spectral clustering algorithm is used for time division. The effectiveness of the method is proved by clustering effect and simulation experiment. Then considering the time series characteristics of traffic flow, the best periodic data is analyzed by order clustering, and the result is better than that of K-means algorithm. In the aspect of coordinating intersection division, this paper first analyzes the calculation model of coordination factor used in Synchro software to describe the correlation of intersection, and then analyzes the steps and methods of dividing coordinated intersection with Synchro software with an example. The simulation results show that the optimal partition can not be obtained directly by Synchro software, and the partition of coordinated intersection has a significant effect on the effect of coordinated control. Then, according to the model of maximum number of intersections, the dividing standard of coordinated intersection is established. The method is simple and effective. In sub-area division, the simulation environment is established by micro-simulation software VISSIM, and the influence of the change of intersection cycle, green signal ratio and saturation on the control scheme and control effect of adjacent intersection is analyzed respectively, in order to understand the correlation of intersection deeply. Then using the community partition algorithm in the complex network, the improved algorithm is applied to the weighted network, and the sub-area partition method of the large-scale traffic network is obtained.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U491.54

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