高速公路異常事件影響范圍演化分析與預(yù)測研究
發(fā)布時間：2019-07-09 07:48
【摘要】：高速公路異常事件會對道路的通行產(chǎn)生較大影響,容易引發(fā)交通擁堵,并沿事發(fā)點(diǎn)上游迅速蔓延,使得道路資源得不到充分利用。因此,盡可能準(zhǔn)確地把握事件影響范圍及其發(fā)展趨勢將有助于提高高速公路的管控和服務(wù)水平。異常事件影響范圍表現(xiàn)為擁堵車流波的傳播范圍。但目前對異常事件下?lián)矶萝嚵鞑ú糠钟绊懸蛩氐姆抡娣治鰞H在單一車型下分析,此外,現(xiàn)有的大多數(shù)基于交通波理論建立的事件影響范圍預(yù)測模型以及異常事件下?lián)矶聽顟B(tài)演化分析方法適用性不強(qiáng)。對此,以高速公路異常事件為研究對象,本文首先對異常事件下?lián)矶萝嚵鞑ㄓ绊懸蛩剡M(jìn)行了分析,其次,結(jié)合交通流時空關(guān)聯(lián)特性,給出了基于云模型及相似序列搜索的事發(fā)點(diǎn)上游流量預(yù)測方法,最后,建立了基于交通波模型及MCTM和云模型的事件影響范圍預(yù)測及演化分析方法。論文主要內(nèi)容包括:①考慮異常事件影響范圍的時空傳播特性,基于時空消耗的思想,應(yīng)用偏微分方法和數(shù)值模擬分析了異常事件的時空影響。結(jié)合VISSIM仿真和實(shí)測數(shù)據(jù),并在仿真中同時考慮大車、小型車,定義表征異常事件擴(kuò)散影響的數(shù)據(jù)“變點(diǎn)”和“變點(diǎn)區(qū)”,并采用單因素置換的分析方法,分析了多種因素對異常事件下?lián)矶萝嚵鞑ǖ挠绊?從而把握異常事件下?lián)矶碌臄U(kuò)散規(guī)律。②針對現(xiàn)有事發(fā)點(diǎn)上游流量預(yù)測方法缺乏考慮交通流時空關(guān)聯(lián)特性的不足,從高速公路交通流的時空關(guān)聯(lián)特性角度出發(fā),同時考慮交通流的不確定性,提出了一種基于云模型及相似序列搜索的事發(fā)點(diǎn)上游流量的預(yù)測方法,通過實(shí)例分析,驗(yàn)證了該方法的有效性。③針對當(dāng)前以交通波理論為基礎(chǔ)建立的異常事件影響范圍預(yù)測模型適用性不強(qiáng)等問題,考慮不同空間背景下交通流的差異性,通過對高速公路實(shí)測數(shù)據(jù)的統(tǒng)計分析,應(yīng)用Van Aerde模型建立了研究路段的交通流模型,并提出了異常事件影響范圍預(yù)測模型,最后通過對典型事件的分析,驗(yàn)證了該模型的可行性。④針對采用閾值劃分的確定性、統(tǒng)一性指標(biāo)難以準(zhǔn)確識別擁堵狀態(tài)的不足,提出了基于MCTM模型及云模型的異常事件下交通擁堵狀態(tài)演化分析方法,利用基于云模型的交通擁堵狀態(tài)估計方法實(shí)現(xiàn)元胞狀態(tài)識別,進(jìn)而應(yīng)用MCTM模型實(shí)現(xiàn)不同時刻擁堵擴(kuò)散范圍的有效估計,并通過實(shí)驗(yàn)驗(yàn)證了方法的合理性和有效性。綜合上述研究,形成了高速公路異常事件影響范圍演化分析與預(yù)測方法,實(shí)驗(yàn)表明,該方法合理、可行、有效,具有一定的應(yīng)用價值。
[Abstract]:The abnormal events of expressway will have a great impact on the traffic of the road, which can easily lead to traffic congestion and spread rapidly along the upstream of the accident point, so that the road resources can not be fully utilized. Therefore, grasping the influence range and development trend of the event as accurately as possible will help to improve the control and service level of expressway. The influence range of abnormal events is the propagation range of congested traffic flow wave. However, at present, the simulation analysis of some influencing factors of traffic congestion flow wave under abnormal events is only under a single vehicle type. In addition, most of the existing event influence range prediction models based on traffic wave theory and the evolution analysis methods of congestion state under abnormal events are not applicable. In this paper, the influencing factors of traffic congestion wave under abnormal events are analyzed in this paper. secondly, combined with the temporal and spatial correlation characteristics of traffic flow, the upstream flow prediction method of incident point based on cloud model and similar sequence search is given. finally, the prediction and evolution analysis method of event influence range based on traffic wave model, MCTM and cloud model is established. The main contents of this paper are as follows: (1) considering the space-time propagation characteristics of the influence range of abnormal events, based on the idea of space-time consumption, the partial differential method and numerical simulation are used to analyze the temporal and spatial effects of abnormal events. Combined with VISSIM simulation and measured data, and considering large car and small vehicle at the same time, the data "variable point" and "variable point area" which characterize the influence of abnormal event diffusion are defined, and the influence of many factors on traffic congestion flow wave under abnormal event is analyzed by using single factor replacement analysis method. In order to grasp the diffusion law of congestion under abnormal events. 2 in view of the lack of considering the temporal and spatial correlation characteristics of traffic flow, a prediction method of upstream traffic flow based on cloud model and similar sequence search is proposed, which is based on cloud model and similar sequence search, from the point of view of temporal and spatial correlation characteristics of expressway traffic flow. The effectiveness of the method is verified. 3 in order to solve the problem that the prediction model of the influence range of abnormal events based on traffic wave theory is not applicable, considering the difference of traffic flow in different spatial backgrounds, through the statistical analysis of the measured data of expressway, the traffic flow model of the research section is established by using Van Aerde model, and the prediction model of the influence range of abnormal events is put forward. Finally, the feasibility of the model is verified by the analysis of typical events. 4 in view of the fact that it is difficult to accurately identify the congestion state by using the certainty of threshold division, the evolution analysis method of traffic congestion state under abnormal events based on MCTM model and cloud model is proposed, and the cellular state identification is realized by using the traffic congestion state estimation method based on cloud model. Furthermore, the MCTM model is used to estimate the congestion diffusion range at different times, and the rationality and effectiveness of the method are verified by experiments. Based on the above research, the evolution analysis and prediction method of the influence range of highway abnormal events is formed. The experimental results show that the method is reasonable, feasible and effective, and has certain application value.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491
本文編號：2511990
[Abstract]:The abnormal events of expressway will have a great impact on the traffic of the road, which can easily lead to traffic congestion and spread rapidly along the upstream of the accident point, so that the road resources can not be fully utilized. Therefore, grasping the influence range and development trend of the event as accurately as possible will help to improve the control and service level of expressway. The influence range of abnormal events is the propagation range of congested traffic flow wave. However, at present, the simulation analysis of some influencing factors of traffic congestion flow wave under abnormal events is only under a single vehicle type. In addition, most of the existing event influence range prediction models based on traffic wave theory and the evolution analysis methods of congestion state under abnormal events are not applicable. In this paper, the influencing factors of traffic congestion wave under abnormal events are analyzed in this paper. secondly, combined with the temporal and spatial correlation characteristics of traffic flow, the upstream flow prediction method of incident point based on cloud model and similar sequence search is given. finally, the prediction and evolution analysis method of event influence range based on traffic wave model, MCTM and cloud model is established. The main contents of this paper are as follows: (1) considering the space-time propagation characteristics of the influence range of abnormal events, based on the idea of space-time consumption, the partial differential method and numerical simulation are used to analyze the temporal and spatial effects of abnormal events. Combined with VISSIM simulation and measured data, and considering large car and small vehicle at the same time, the data "variable point" and "variable point area" which characterize the influence of abnormal event diffusion are defined, and the influence of many factors on traffic congestion flow wave under abnormal event is analyzed by using single factor replacement analysis method. In order to grasp the diffusion law of congestion under abnormal events. 2 in view of the lack of considering the temporal and spatial correlation characteristics of traffic flow, a prediction method of upstream traffic flow based on cloud model and similar sequence search is proposed, which is based on cloud model and similar sequence search, from the point of view of temporal and spatial correlation characteristics of expressway traffic flow. The effectiveness of the method is verified. 3 in order to solve the problem that the prediction model of the influence range of abnormal events based on traffic wave theory is not applicable, considering the difference of traffic flow in different spatial backgrounds, through the statistical analysis of the measured data of expressway, the traffic flow model of the research section is established by using Van Aerde model, and the prediction model of the influence range of abnormal events is put forward. Finally, the feasibility of the model is verified by the analysis of typical events. 4 in view of the fact that it is difficult to accurately identify the congestion state by using the certainty of threshold division, the evolution analysis method of traffic congestion state under abnormal events based on MCTM model and cloud model is proposed, and the cellular state identification is realized by using the traffic congestion state estimation method based on cloud model. Furthermore, the MCTM model is used to estimate the congestion diffusion range at different times, and the rationality and effectiveness of the method are verified by experiments. Based on the above research, the evolution analysis and prediction method of the influence range of highway abnormal events is formed. The experimental results show that the method is reasonable, feasible and effective, and has certain application value.
【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491
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