發(fā)布時(shí)間：2018-07-13 17:41

【摘要】：智能交通系統(tǒng)(ITS)作為一種現(xiàn)在全世界公認(rèn)有效的交通需求管理方式,對(duì)緩解城市交通擁堵問(wèn)題具有相當(dāng)顯著的作用。基于智能交通系統(tǒng)技術(shù)的受控路網(wǎng)正逐漸顯露出來(lái)。受控路網(wǎng)為交通流運(yùn)行方式基于網(wǎng)絡(luò)平臺(tái)的重建提供了現(xiàn)實(shí)基礎(chǔ)。本文根據(jù)受控路網(wǎng)的特點(diǎn)構(gòu)建了受控路網(wǎng)條件下的動(dòng)態(tài)交通分配模型,將控制思想融入動(dòng)態(tài)交通分配中,且不同于傳統(tǒng)動(dòng)態(tài)交通分配模型最終得到的唯一最優(yōu)狀態(tài),論文實(shí)現(xiàn)了在受控路網(wǎng)下對(duì)道路流量進(jìn)行有控制的分配的目標(biāo),使得路網(wǎng)可以按照管理者的意愿或路網(wǎng)的實(shí)際情況進(jìn)行更為合理的動(dòng)態(tài)配流,完成了對(duì)路網(wǎng)流量的定時(shí)定量控制。并通過(guò)路段流量控制達(dá)到改善路網(wǎng)均衡狀態(tài)、減少局部交通擁堵、提高城市交通系統(tǒng)運(yùn)行效率的目的。本文首先結(jié)合智能交通技術(shù)對(duì)受控路網(wǎng)進(jìn)行了全面的介紹和分析,包括其網(wǎng)絡(luò)特性和對(duì)動(dòng)態(tài)交通分配的影響,確定了受控路網(wǎng)條件下的路徑選擇及其分配方法。然后對(duì)影響路網(wǎng)整體運(yùn)行效率的關(guān)鍵路段進(jìn)行分析,根據(jù)其在路網(wǎng)中的地位和動(dòng)態(tài)交通分配中的作用給出了其識(shí)別步驟。其次,針對(duì)受控路網(wǎng)條件下關(guān)鍵路段流量的控制,考慮到流量分配的延時(shí)性,即分配后流量在路段上會(huì)有一段運(yùn)行時(shí)間,本文提出一種預(yù)控制方式即提前控制將要到達(dá)關(guān)鍵路段上的流量,使得流量在任意時(shí)刻都不會(huì)超過(guò)限定值。據(jù)此利用BP神經(jīng)網(wǎng)絡(luò)對(duì)受限路段上的流量進(jìn)行預(yù)測(cè),得到流量達(dá)到飽和值的時(shí)刻然后根據(jù)走行時(shí)間進(jìn)行逆推得到應(yīng)該進(jìn)行控制的時(shí)刻。最后,結(jié)合以上分析,以系統(tǒng)最優(yōu)為目標(biāo),基于最優(yōu)控制理論建立了受控路網(wǎng)條件下的動(dòng)態(tài)交通分配模型。分析了模型的最優(yōu)解條件并闡述了模型的求解算法。以一較大網(wǎng)絡(luò)作為路網(wǎng)算例,進(jìn)行了不同OD需求下以及有無(wú)流量限制的分配,最后分配結(jié)果表明在對(duì)關(guān)鍵路段進(jìn)行流量控制的情況下關(guān)鍵路段流量能夠合理分流到其他路段上,路段的運(yùn)行效率能夠維持在一個(gè)比較穩(wěn)定的水平,有效地避免了局部交通擁堵和潛在的網(wǎng)絡(luò)格鎖。
[Abstract]:Intelligent Transportation system (its), as an effective way of traffic demand management, plays a significant role in alleviating urban traffic congestion. The controlled road network based on Intelligent Transportation system (its) technology is gradually emerging. The controlled road network provides a practical basis for the reconstruction of traffic flow operation mode based on network platform. According to the characteristics of the controlled road network, this paper constructs the dynamic traffic assignment model under the condition of the controlled road network, and integrates the control idea into the dynamic traffic distribution, which is different from the only optimal state finally obtained by the traditional dynamic traffic assignment model. The paper realizes the goal of the controlled distribution of the road flow under the controlled road network, which makes the road network more reasonable dynamic flow allocation according to the wishes of the manager or the actual situation of the road network. The timing and quantitative control of network flow is completed. The road flow control can improve the equilibrium state of the road network, reduce the local traffic congestion and improve the efficiency of the urban traffic system. This paper first introduces and analyzes the controlled road network with intelligent transportation technology, including its network characteristics and its influence on dynamic traffic allocation, and determines the route selection and its allocation method under the condition of controlled road network. Then the key sections which affect the overall operation efficiency of the road network are analyzed and the identification steps are given according to their position in the road network and the role of dynamic traffic assignment. Secondly, considering the delay of flow distribution, that is to say, the flow will have a period of running time in the road section after the flow distribution is considered for the control of the critical road flow under the condition of controlled road network. In this paper, a precontrol method is proposed, that is, the flow will reach the critical section in advance, so that the flow will not exceed the limited value at any time. The BP neural network is used to predict the flow on the restricted road, and the time when the flow reaches saturation value is obtained, and then the time of control is obtained according to the travel time. Finally, based on the optimal control theory, the dynamic traffic assignment model under the condition of controlled road network is established based on the above analysis. The optimal solution condition of the model is analyzed and the algorithm of solving the model is described. Taking a large network as an example, the assignment of different OD demand and no flow restriction is carried out. The results show that the flow of key sections can be reasonably diverted to other sections under the condition of controlling the flow of critical sections. The operation efficiency of road sections can be maintained at a relatively stable level, effectively avoiding local traffic jams and potential network latches.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U491

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