基于復(fù)雜網(wǎng)絡(luò)的突發(fā)事件VMS信息發(fā)布特性研究
發(fā)布時(shí)間：2018-08-06 15:26
【摘要】：可變信息情報(bào)板(VMS)作為城市交通動(dòng)態(tài)信息發(fā)布的重要方式,對(duì)緩解城市路網(wǎng)中由突發(fā)事件而引起的交通擁堵,發(fā)揮著非常重要的作用。由于交通流的隨機(jī)性以及可能引起的信息集中或過剩等原因,使得VMS誘導(dǎo)效果并不顯著,甚至造成負(fù)面影響。因此,有必要對(duì)VMS信息發(fā)布策略的特征進(jìn)行研究,復(fù)雜網(wǎng)絡(luò)方法為城市路網(wǎng)中這一研究提供了了一個(gè)新視角。 本文定義了可以反映VMS顯示屏之間相關(guān)關(guān)系的概念-VMS關(guān)聯(lián)度,并應(yīng)用復(fù)雜網(wǎng)絡(luò)的相關(guān)知識(shí),構(gòu)建了的VMS關(guān)聯(lián)性網(wǎng)絡(luò)模型,提出了VMS關(guān)聯(lián)網(wǎng)絡(luò)的統(tǒng)計(jì)分析方法。以北京市VMS信息發(fā)布為背景,針對(duì)主要包括事故和故障車事件的突發(fā)事件,分別構(gòu)建了早高峰和晚高峰時(shí)段的事故VMS關(guān)聯(lián)網(wǎng)絡(luò)和故障車VMS關(guān)聯(lián)網(wǎng)絡(luò),通過研究VMS關(guān)聯(lián)網(wǎng)絡(luò)的性質(zhì)得到了北京市事故和故障車VMS信息發(fā)布的空間特征規(guī)律,從而為VMS信息發(fā)布策略的制定與優(yōu)化提供支持。 首先,通過對(duì)事故網(wǎng)絡(luò)和故障車網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu)分析發(fā)現(xiàn),二種網(wǎng)絡(luò)均表現(xiàn)出了明顯的小世界特性,即交通流的連續(xù)性使得各VMS顯示屏之間的具有明顯的關(guān)聯(lián)性。事故信息的發(fā)布范圍會(huì)受到交通流狀況的影響,而故障車事件則相關(guān)性不大。雖然故障車網(wǎng)絡(luò)的連通性遠(yuǎn)遠(yuǎn)不如事故網(wǎng)絡(luò),但其集團(tuán)性明顯高于事故信息網(wǎng)絡(luò),這與統(tǒng)計(jì)出的故障車信息的發(fā)布范圍明顯小于事故信息的發(fā)布范圍是一致的。 其次,論文統(tǒng)計(jì)了網(wǎng)絡(luò)的加權(quán)指標(biāo),包括邊權(quán)、點(diǎn)權(quán)和單位權(quán),得到了事故和故障車的發(fā)生在地域上的偶然性很大,早晚高峰時(shí)段事故的嚴(yán)重程度地域分布差別比較大,存在受事故影響較為嚴(yán)重的區(qū)域的結(jié)論,并且發(fā)現(xiàn)事故網(wǎng)絡(luò)的關(guān)鍵點(diǎn)早高峰更加分散,而晚高峰則相對(duì)集中；故障車在網(wǎng)絡(luò)在早高峰和晚高峰的關(guān)鍵點(diǎn)分布都較為分散。之后,論文對(duì)網(wǎng)絡(luò)的度、單位權(quán)和點(diǎn)權(quán)進(jìn)行相關(guān)性分析,在此基礎(chǔ)上對(duì)于不同的VMS信息顯示屏,根據(jù)度、單位權(quán)、點(diǎn)權(quán)和聚類系數(shù)四個(gè)屬性進(jìn)行了聚類分析,將VMS劃分為16個(gè)類別,每個(gè)類別分別對(duì)應(yīng)一種VMS信息發(fā)布特性,并給出了早晚高峰時(shí)段事故和故障車網(wǎng)絡(luò)中D、E類的顯示屏分布圖。 最后,論文將VMS關(guān)聯(lián)網(wǎng)絡(luò)劃分為派系,進(jìn)行了社團(tuán)結(jié)構(gòu)挖掘,挖掘出了VMS信息發(fā)布的組團(tuán)性質(zhì),并利用模塊度對(duì)劃分結(jié)果進(jìn)行評(píng)估和優(yōu)化。研究發(fā)現(xiàn),事故網(wǎng)絡(luò)和早高峰時(shí)段的故障車網(wǎng)絡(luò)的模塊度均小于0,在分析原因后論文對(duì)社團(tuán)結(jié)構(gòu)的劃分進(jìn)行了人工優(yōu)化,優(yōu)化后的網(wǎng)絡(luò)模塊度指標(biāo)更加符合VMS關(guān)聯(lián)網(wǎng)絡(luò)屬于混合網(wǎng)絡(luò)這一事實(shí)。優(yōu)化后的社團(tuán)結(jié)構(gòu)劃分結(jié)果可作為VMS信息發(fā)布的參考策略。
[Abstract]:Variable information board (VMS), as an important way to issue urban traffic dynamic information, plays a very important role in alleviating traffic congestion caused by unexpected events in urban road network. Due to the randomness of traffic flow and the possible information concentration or excess, the induction effect of VMS is not significant or even negative. Therefore, it is necessary to study the characteristics of VMS information release strategy, and the complex network method provides a new perspective for the study of urban road network. This paper defines the concept of -VMS correlation degree which can reflect the correlation relationship between VMS display screens, and applies the related knowledge of complex network to construct the VMS correlation network model, and puts forward the statistical analysis method of VMS correlation network. Based on the information release of Beijing VMS, this paper constructs the accident VMS connection network and the fault vehicle VMS associated network during the morning rush hour and the late rush hour, respectively, in view of the emergency events which mainly include the accident and the malfunction vehicle event. By studying the properties of VMS related network, the spatial characteristics of VMS information release of Beijing accident and fault vehicles are obtained, which can support the formulation and optimization of VMS information release strategy. Firstly, by analyzing the topology of the accident network and the vehicle network, it is found that the two networks have obvious small-world characteristics, that is, the continuity of the traffic flow makes the VMS display screen have obvious correlation. The range of accident information is affected by the traffic flow, but the accident is not relevant. Although the connectivity of the fault vehicle network is far less than that of the accident network, its collectivity is obviously higher than that of the accident information network, which is consistent with the statistical distribution range of the fault vehicle information is obviously smaller than that of the accident information. Secondly, the paper statistics the weighted index of the network, including side weight, point weight and unit weight, and obtains that the accident and fault vehicle occurrence in the region is very accidental, and the regional distribution of the accident severity in the morning and evening rush hour is quite different. It is found that the key points of the accident network are more dispersed in the early peak, while the late peak is relatively concentrated, and the distribution of the fault car in the critical points of the early peak and the late peak in the network is more dispersed. After that, the paper analyzes the correlation among the degree, unit weight and point weight of the network. On this basis, for different VMS information display, according to the four attributes of degree, unit weight, point weight and clustering coefficient, cluster analysis is carried out. The VMS is divided into 16 categories, each category corresponds to one kind of VMS information release characteristic, and the display screen distribution diagram of VMS E in the morning and evening rush hour accident and fault vehicle network is given. Finally, the paper divides the VMS association network into factions, mining the community structure, mining the group nature of VMS information publishing, and evaluating and optimizing the partition result by modularity. It is found that the modular degree of the accident network and the fault car network in the early rush hour is less than 0. After analyzing the reasons, the paper makes a manual optimization to the division of the community structure. The optimized network module index is more in line with the fact that the VMS network belongs to the hybrid network. The optimized community structure partition results can be used as a reference strategy for VMS information publishing.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U492.8
本文編號(hào)：2168149
[Abstract]:Variable information board (VMS), as an important way to issue urban traffic dynamic information, plays a very important role in alleviating traffic congestion caused by unexpected events in urban road network. Due to the randomness of traffic flow and the possible information concentration or excess, the induction effect of VMS is not significant or even negative. Therefore, it is necessary to study the characteristics of VMS information release strategy, and the complex network method provides a new perspective for the study of urban road network. This paper defines the concept of -VMS correlation degree which can reflect the correlation relationship between VMS display screens, and applies the related knowledge of complex network to construct the VMS correlation network model, and puts forward the statistical analysis method of VMS correlation network. Based on the information release of Beijing VMS, this paper constructs the accident VMS connection network and the fault vehicle VMS associated network during the morning rush hour and the late rush hour, respectively, in view of the emergency events which mainly include the accident and the malfunction vehicle event. By studying the properties of VMS related network, the spatial characteristics of VMS information release of Beijing accident and fault vehicles are obtained, which can support the formulation and optimization of VMS information release strategy. Firstly, by analyzing the topology of the accident network and the vehicle network, it is found that the two networks have obvious small-world characteristics, that is, the continuity of the traffic flow makes the VMS display screen have obvious correlation. The range of accident information is affected by the traffic flow, but the accident is not relevant. Although the connectivity of the fault vehicle network is far less than that of the accident network, its collectivity is obviously higher than that of the accident information network, which is consistent with the statistical distribution range of the fault vehicle information is obviously smaller than that of the accident information. Secondly, the paper statistics the weighted index of the network, including side weight, point weight and unit weight, and obtains that the accident and fault vehicle occurrence in the region is very accidental, and the regional distribution of the accident severity in the morning and evening rush hour is quite different. It is found that the key points of the accident network are more dispersed in the early peak, while the late peak is relatively concentrated, and the distribution of the fault car in the critical points of the early peak and the late peak in the network is more dispersed. After that, the paper analyzes the correlation among the degree, unit weight and point weight of the network. On this basis, for different VMS information display, according to the four attributes of degree, unit weight, point weight and clustering coefficient, cluster analysis is carried out. The VMS is divided into 16 categories, each category corresponds to one kind of VMS information release characteristic, and the display screen distribution diagram of VMS E in the morning and evening rush hour accident and fault vehicle network is given. Finally, the paper divides the VMS association network into factions, mining the community structure, mining the group nature of VMS information publishing, and evaluating and optimizing the partition result by modularity. It is found that the modular degree of the accident network and the fault car network in the early rush hour is less than 0. After analyzing the reasons, the paper makes a manual optimization to the division of the community structure. The optimized network module index is more in line with the fact that the VMS network belongs to the hybrid network. The optimized community structure partition results can be used as a reference strategy for VMS information publishing.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U492.8
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