本文選題：高速公路 + 幾何線形條件　； 參考：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：道路條件是交通事故發(fā)生的重要原因。其中,交通量和幾何線形是造成事故的關(guān)鍵道路交通條件,此方面相關(guān)的研究已經(jīng)取得很多成果。除此之外,道路路表性能也是影響交通事故的重要道路條件,但由于路表性能數(shù)據(jù)的難獲得,此方面相關(guān)的研究進展不多。目前,大數(shù)據(jù)的發(fā)展和道路檢測技術(shù)的規(guī)范化使得路表性能數(shù)據(jù)已可大量獲取,由此本文構(gòu)建包含道路交通條件和路表性能條件的高速公路事故預(yù)測模型。常用路表性能指標有五類,分別為路面行駛質(zhì)量指數(shù)、路面損壞狀況指數(shù)、路面結(jié)構(gòu)強度指數(shù)、路面抗滑性能指數(shù)及路面車轍深度指數(shù),本文路表性能指標均從0至100取值,分別表示理論上的最差和最好的路表性能。本文通過分析高速公路的道路交通條件和路表性能條件,建立交通事故預(yù)測模型。首先,以遼寧省沈山高速公路作為本文研究對象,對路段單元的交通量數(shù)據(jù)、道路幾何線形數(shù)據(jù)、路表性能指標數(shù)據(jù)和交通事故數(shù)據(jù)進行整理分析;分析常用路段劃分方法,確定用同質(zhì)法劃分沈山高速公路路段,為事故預(yù)測提供基本研究單元。其次,對常用事故預(yù)測模型的主要型式及適用性進行了分析,根據(jù)高速公路交通事故數(shù)據(jù)的統(tǒng)計分布特征,確定了本文選用的事故預(yù)測模型形式為負二項分布;選擇了對道路交通安全有顯著影響的交通量、道路幾何線形指標和路表性能指標作為事故預(yù)測模型的自變量,路段每年事故率作為因變量,依據(jù)95%置信水平,構(gòu)建了本文的負二項分布事故預(yù)測模型。然后,依據(jù)敏感性分析的原理,計算各個事故影響因素的相對敏感性系數(shù),根據(jù)結(jié)果分析了變量的影響程度;再分析研究道路幾何線形指標和路表性能指標與事故率的關(guān)系,得出指標的優(yōu)化值。最后,以沈山高速公路部分數(shù)據(jù)為例,對本文的負二項事故預(yù)測模型進行驗證研究,計算所建模型的預(yù)測精度;以廣東省粵贛高速公路作為案例,對本文的事故預(yù)測模型進行應(yīng)用,并通過實際事故數(shù)驗證模型精度,表明本文所建負二項模型具有一定的適應(yīng)性,然后對廣東省粵贛高速公路未來年事故數(shù)進行預(yù)測。
[Abstract]:Road condition is an important cause of traffic accidents. Among them, traffic volume and geometric alignment are the key road traffic conditions, and many achievements have been made in this field. In addition, the performance of road surface is also an important condition affecting traffic accidents. However, due to the difficulty of obtaining the performance data of road surface, there is not much research progress in this area. At present, with the development of big data and the standardization of road detection technology, the road table performance data can be obtained in large quantities. Therefore, this paper constructs a highway accident prediction model which includes road traffic conditions and road surface performance conditions. There are five kinds of road surface performance indexes in common use, which are road quality index, pavement damage condition index, pavement structure strength index, pavement anti-skid performance index and rutting depth index. The performance index of this paper is from 0 to 100. Represents the worst and best performance in theory, respectively. In this paper, the traffic accident prediction model is established by analyzing the road traffic condition and the performance condition of highway surface. First of all, taking Shenshan Expressway in Liaoning Province as the research object, the traffic volume data, road geometry line data, road surface performance index data and traffic accident data are analyzed. The homogeneous method is used to divide the section of Shenshan Expressway, which provides the basic research unit for accident prediction. Secondly, the main types and applicability of common accident prediction models are analyzed. According to the statistical distribution characteristics of expressway traffic accident data, the accident prediction model selected in this paper is negative binomial distribution. The traffic volume, road geometric line index and road surface performance index, which have significant influence on road traffic safety, are selected as independent variables of accident prediction model, and the accident rate of road sections is taken as dependent variable, according to 95% confidence level, the traffic volume, road surface performance index and road surface performance index are selected as independent variables of accident prediction model. The negative binomial distribution accident prediction model is constructed in this paper. Then, according to the principle of sensitivity analysis, the relative sensitivity coefficient of each accident influencing factor is calculated, the influence degree of the variable is analyzed according to the result, and the relationship between the road geometry linear index and the road surface performance index and the accident rate is analyzed. The optimum value of the index is obtained. Finally, taking some data of Shenshan Expressway as an example, the negative binomial accident prediction model of this paper is verified and studied to calculate the prediction accuracy of the established model, and the Guangdong Guangdong-Jiangxi Expressway is taken as a case study. The application of the accident prediction model in this paper is carried out, and the accuracy of the model is verified by the actual accident number, which shows that the negative binomial model established in this paper has certain adaptability, and then forecasts the number of accidents in the future of Guangdong Guangdong province expressway.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U491.3

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