高速公路异常事件影响范围演化分析与预测研究
[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.
【学位授予单位】:重庆大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:U491
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