【摘要】：隨著社會(huì)的高速發(fā)展,交通擁堵問(wèn)題嚴(yán)重的影響了國(guó)家城市化的進(jìn)程。智能交通系統(tǒng)作為一門(mén)新興的研究課題,為解決城市交通擁堵問(wèn)題提供了新的解決方案。交通控制和車(chē)輛誘導(dǎo)作為智能交通系統(tǒng)的兩個(gè)重要組成部分,在解決城市交通擁堵問(wèn)題上越來(lái)越受到關(guān)注和重視。在現(xiàn)有的智能交通系統(tǒng)研究中,主要利用交通控制子系統(tǒng)對(duì)路況進(jìn)行處理,而車(chē)輛誘導(dǎo)子系統(tǒng)完成對(duì)車(chē)輛的路徑規(guī)劃,大多偏重于對(duì)交通燈控制和車(chē)輛誘導(dǎo)的分開(kāi)研究。但是在實(shí)際的城市交通路網(wǎng)中,通過(guò)將交通燈控制與車(chē)輛誘導(dǎo)進(jìn)行集成,能夠進(jìn)一步促進(jìn)道路擁堵的疏散,且有助于提高出行者的行車(chē)效率。本文針對(duì)交通燈控制與車(chē)輛誘導(dǎo)的集成進(jìn)行了研究,針對(duì)車(chē)輛誘導(dǎo)的具體實(shí)現(xiàn)場(chǎng)景,提出了基于交通燈配置的車(chē)輛誘導(dǎo)機(jī)制,該車(chē)輛誘導(dǎo)機(jī)制主要通過(guò)兩個(gè)步驟來(lái)完成對(duì)路網(wǎng)中道路擁堵的消散以及車(chē)輛的誘導(dǎo)調(diào)度,這兩個(gè)步驟分別是:(1)路網(wǎng)流量均衡策略:根據(jù)交通的動(dòng)態(tài)路況自動(dòng)配置交通燈的綠信比,完成對(duì)擁堵道路的疏散;(2)路網(wǎng)流量?jī)?yōu)化分配策略:對(duì)全網(wǎng)車(chē)輛進(jìn)行誘導(dǎo)分配,達(dá)到整個(gè)路網(wǎng)中車(chē)輛總行駛時(shí)間最少。通過(guò)MATLAB仿真工具,對(duì)基于交通燈配置的車(chē)輛誘導(dǎo)機(jī)制進(jìn)行了仿真,并比較分析了車(chē)輛誘導(dǎo)前后路網(wǎng)中平均飽和度、飽和度方差、全網(wǎng)車(chē)輛行駛時(shí)間等參數(shù)變化情況,實(shí)驗(yàn)結(jié)果表明,通過(guò)基于交通燈配置的車(chē)輛誘導(dǎo)機(jī)制能夠有效地降低路網(wǎng)中的平均飽和度及飽和度方差,均衡整個(gè)路網(wǎng)的交通流量,同時(shí)能夠降低全網(wǎng)車(chē)輛的總行駛時(shí)間,提高了路網(wǎng)的通行能力。此外,本文將交通燈調(diào)整時(shí)間作為車(chē)輛誘導(dǎo)算法中的一個(gè)時(shí)間因子,進(jìn)一步提出了基于交通燈配置的車(chē)輛誘導(dǎo)算法ED*算法,通過(guò)車(chē)輛ED*誘導(dǎo)算法完成對(duì)路網(wǎng)中的車(chē)輛個(gè)體進(jìn)行誘導(dǎo),完成對(duì)其出行路徑的動(dòng)態(tài)規(guī)劃,以達(dá)到使微觀車(chē)輛個(gè)體行駛時(shí)間最少的目的。通過(guò)VC++6.0完成了對(duì)ED*車(chē)輛誘導(dǎo)算法的計(jì)算及仿真,并與A*算法、D*Lite算法進(jìn)行比較,實(shí)驗(yàn)結(jié)果表明,在路況信息發(fā)生變化后,ED*算法在重新規(guī)劃路徑的計(jì)算速度上具有顯著的提高,有助于提高路網(wǎng)中車(chē)輛的行駛效率,適用于城市動(dòng)態(tài)交通路網(wǎng)。
[Abstract]:With the rapid development of society, traffic congestion has seriously affected the process of urbanization. As a new research subject, Intelligent Transportation system (its) provides a new solution to the problem of urban traffic congestion. Traffic control and vehicle guidance, as two important components of intelligent transportation system, have been paid more and more attention to in solving the problem of urban traffic congestion. In the existing research of Intelligent Transportation system, the traffic control subsystem is mainly used to deal with the road conditions, while the vehicle guidance subsystem completes the path planning of vehicles, most of which focus on the separate study of traffic light control and vehicle guidance. But in the actual urban traffic network, by integrating traffic light control with vehicle guidance, the evacuation of traffic congestion can be further promoted, and the efficiency of travelers can be improved. In this paper, the integration of traffic light control and vehicle guidance is studied, and the vehicle guidance mechanism based on traffic light configuration is proposed. The vehicle induction mechanism mainly completes the dissipation of road congestion and the induced scheduling of vehicles in the road network through two steps. The two steps are as follows: (1) the strategy of road network flow balance: according to the dynamic traffic conditions, the green signal ratio of traffic lights is automatically configured to complete the evacuation of congested roads; (2) the optimal allocation strategy of road network flow: the inductive allocation of the whole network vehicles, The total vehicle travel time is the least in the whole road network. Through MATLAB simulation tool, the vehicle guidance mechanism based on traffic light configuration is simulated, and the variation of average saturation, saturation variance, vehicle travel time and so on in the road network before and after vehicle guidance are compared and analyzed. The experimental results show that the vehicle guidance mechanism based on traffic light configuration can effectively reduce the average saturation and saturation variance in the road network, balance the traffic flow of the whole network, and reduce the total travel time of the whole network vehicle at the same time. The capacity of the road network has been improved. In addition, the traffic light adjustment time is taken as a time factor in the vehicle guidance algorithm, and an ED* algorithm based on traffic light configuration is proposed. In order to achieve the goal of minimizing the driving time of individual vehicles in the road network, an ED* guidance algorithm is used to guide the individual vehicles in the road network and to complete the dynamic planning of their travel paths. Through VC 6.0, the calculation and simulation of ED* vehicle guidance algorithm are completed, and compared with the A* algorithm, the experimental results show that after the change of road condition information, the calculation speed of ED* algorithm is significantly improved in re-planning the path. It is helpful to improve the driving efficiency of vehicles in the road network and is suitable for the urban dynamic traffic network.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：U495

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 劉寧;城市道路阻抗模型的研究與應(yīng)用[D];大連理工大學(xué);2012年

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本文編號(hào)：2131264