本文關(guān)鍵詞：公路隧道交通安全狀態(tài)特征選擇與評估方法研究　出處：《福州大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 公路隧道 交通安全狀態(tài) 評估方法 模糊C均值聚類 神經(jīng)網(wǎng)絡(luò)模式識別

【摘要】：隨著公路建設(shè)事業(yè)的快速發(fā)展,交通安全隱患逐漸成為社會關(guān)注的重點對象之一。公路隧道作為路段的重要構(gòu)造物,若出現(xiàn)交通事故,會影響車輛的正常行駛甚至導(dǎo)致整個路網(wǎng)的癱瘓,因此,保障公路隧道的運(yùn)營安全,對維持社會、經(jīng)濟(jì)的穩(wěn)定發(fā)展都極其重要。鑒于交通安全的日趨重要性以及公路隧道監(jiān)控系統(tǒng)的日趨完善,若能通過智能控制的方法,建立一個公路隧道的安全評價體系,對公路隧道的交通安全性能進(jìn)行評價,對于減少工作人員的工作量和工作難度和方便駕駛員及時獲取隧道的安全狀況,都有很重要的現(xiàn)實意義。本文圍繞公路隧道交通安全狀態(tài)的特征選擇和評估方法進(jìn)行研究。首先,對尚不成熟的交通安全狀態(tài)的概念進(jìn)行定義的解釋與特點分析,并說明其在公路隧道交通安全評價中的應(yīng)用；接著,介紹公路隧道事故特性和危害,以及目前常用的隧道交通安全評價指標(biāo),根據(jù)已有的道路評價方法的分類,確定公路隧道交通安全狀態(tài)的分類標(biāo)準(zhǔn)。在對公路隧道交通安全特性進(jìn)行分析的基礎(chǔ)上,研究公路隧道交通安全狀態(tài)的特征參數(shù)。首先,將隧道事故交通流與vissim事故仿真的交通流結(jié)果進(jìn)行比較,確定使用vissim交通仿真模擬隧道的事故狀態(tài)的可行性,解決隧道事故的交通流數(shù)據(jù)獲取困難的問題,為后續(xù)的事故研究提供數(shù)據(jù)基礎(chǔ)；接著,對隧道事故的交通流進(jìn)行分析,確定了能用微觀交通流參數(shù)反映隧道環(huán)境變化的事實,從而確定公路隧道交通安全狀態(tài)的特征參數(shù)。在確定特征參數(shù)的基礎(chǔ)上,對公路隧道交通安全狀態(tài)的評估方法進(jìn)行研究。本文分別建立了以模糊C均值聚類算法為基礎(chǔ)的評估模型和以神經(jīng)網(wǎng)絡(luò)模式識別方法為基礎(chǔ)的評估模型,分析這兩個模型對實際隧道交通安全狀態(tài)的評估結(jié)果。結(jié)果顯示,以模糊C均值聚類算法建立的評估模型有自動處理數(shù)據(jù)的優(yōu)點,然而該方法需要以大量的數(shù)據(jù)為基礎(chǔ),并且容易陷入局部最優(yōu)解；以神經(jīng)網(wǎng)絡(luò)模式識別方法建立的評估模型,充分發(fā)揮人的主觀能動性,使評估結(jié)果準(zhǔn)確性更高,但相較于上一個方法則缺少自動分類的便利。
[Abstract]:With the rapid development of highway construction, traffic safety hidden danger has gradually become one of the key objects of social concern. Highway tunnel as an important structure of road section, if there are traffic accidents. Will affect the normal driving of vehicles and even lead to the paralysis of the entire road network, therefore, to ensure the safety of the operation of road tunnels, to maintain the society. The steady development of economy is extremely important. In view of the increasing importance of traffic safety and the improvement of highway tunnel monitoring system, if we can establish a highway tunnel safety evaluation system through the method of intelligent control. To evaluate the traffic safety performance of the highway tunnel, it can reduce the workload and difficulty of the staff and facilitate the drivers to obtain the tunnel safety condition in time. This paper focuses on the characteristics selection and evaluation methods of road tunnel traffic safety status. First of all. The definition and characteristics of the immature concept of traffic safety state are explained, and its application in highway tunnel traffic safety evaluation is explained. Then, it introduces the characteristics and hazards of highway tunnel accidents, as well as the current commonly used tunnel traffic safety evaluation indicators, according to the existing road evaluation methods classification. On the basis of analyzing the traffic safety characteristics of highway tunnel, the characteristic parameters of road tunnel traffic safety state are studied. Comparing the traffic flow of tunnel accident with that of vissim accident simulation, the feasibility of using vissim traffic simulation to simulate tunnel accident state is determined. To solve the difficult problem of obtaining traffic flow data of tunnel accident, and provide the data basis for the subsequent accident research; Then, the traffic flow of tunnel accident is analyzed, and the fact that the microscopic traffic flow parameters can reflect the change of tunnel environment is determined. In order to determine the road tunnel traffic safety state of the characteristic parameters, on the basis of determining the characteristics of the parameters. In this paper, the evaluation model based on fuzzy C-means clustering algorithm and the evaluation model based on neural network pattern recognition method are established, respectively. The results show that the evaluation model based on fuzzy C-means clustering algorithm has the advantage of automatically processing the data. However, this method needs to be based on a large amount of data, and it is easy to fall into the local optimal solution. The evaluation model established by the neural network pattern recognition method can give full play to the subjective initiative of human beings and make the evaluation results more accurate. However, compared with the previous method, the evaluation model lacks the convenience of automatic classification.
【學(xué)位授予單位】：福州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U458

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本文編號：1437532