基于浮动车数据的桥下积水导致的城市快速路交通拥堵规律研究
本文选题:桥下积水 切入点:交通拥堵 出处:《北京交通大学》2014年硕士论文 论文类型:学位论文
【摘要】:近年来,因雨雪等恶劣天气造成的交通拥堵频发,这不仅导致路网大范围交通拥堵事件发生,还造成了严重的经济财产损失,如何应对恶劣天气造成的桥下积水交通拥堵已成为北京等城市面临的新难题。目前,学者和专家对常发性交通拥堵的各方面研究较多,而利用浮动车数据针对暴雨天气这一具体原因所导致的偶发性交通拥堵研究相对较少。在此背景下,本文以北京市为例,针对重点桥下积水道路开展了多角度的浮动车数据分析,归纳总结桥下积水交通拥堵演变规律。在此基础上,提出了基于三个指标的桥下积水交通拥堵点段识别方法,构建了桥下积水交通拥堵的蔓延和消散速度模型。 首先,从交通拥堵定义和交通拥堵特性入手,论述了道路交通运行等级速度划分以及常发性拥堵与偶发性拥堵的异同点。然后,在国内外交通事件自动检测及拥堵点段识别的研究基础上,分析了国内外交通事件自动检测方法在桥下积水交通拥堵识别的适应性。结合现有的交通拥堵特性,同时开展了恶劣天气对交通影响的研究综述。基于此,明确了本文研究的目标、思路和技术路线。 其次,对比分析正常情况和积水当日的交通流数据特性,发现了桥下积水交通拥堵会导致浮动车样本量显著缺失的特征,并提出了浮动车数据样本量比率概念。同时,对比分析了积水交通拥堵与交通事故、交通管制的样本量比率异同点,结果表明,北京市西三环快速路的缺失样本量比例近达80%,西四环快速路的缺失样本量比例高达97%。然后,通过计算分析桥下积水交通拥堵的蔓延和消散速度以及拥堵路段的车辆行驶里程(VKT),归纳总结了桥下积水深度与拥堵蔓延的时间关系规律和拥堵空间的影响范围。 最后,根据桥下积水交通拥堵的空间影响范围、拥堵路段的速度变化和时空分布情况,提出了基于样本量比率、交通流速度变化和速度差三个识别指标的桥下积水交通拥堵点段识别方法,并实现了基于ArcGIS的拥堵点段程序化应用识别。然后,在综合考虑积水当日交通流特性、桥下积水对道路通行能力的折减、通行能力与交通流量比、快速路出入口等影响因素的基础上,并结合逻辑判断和实际经验,初步建立了桥下积水交通拥堵的蔓延和消散速度模型。同时,基于VISSIM仿真数据和积水当日的浮动车数据,对模型参数进行了初步标定。
[Abstract]:In recent years, traffic jams caused by bad weather, such as rain and snow, have occurred frequently, which not only led to large-scale traffic congestion in the road network, but also caused serious economic and property losses. How to deal with traffic jams under bridges caused by bad weather has become a new problem for Beijing and other cities. At present, scholars and experts have studied many aspects of regular traffic jams. However, there are relatively few studies on accidental traffic congestion caused by heavy rain weather using floating vehicle data. In this context, this paper takes Beijing as an example. A multi-angle floating vehicle data analysis is carried out for the waterlogged road under the key bridge, and the evolution law of the traffic congestion under the bridge is summarized. On the basis of this, a method of identifying the traffic jams under the bridge is proposed based on three indexes. The speed model of spreading and dissipating traffic congestion under the bridge is constructed. First of all, starting with the definition of traffic congestion and traffic congestion characteristics, the paper discusses the speed division of traffic grade and the similarities and differences between regular traffic congestion and accidental congestion. Based on the research of automatic detection of traffic events and identification of traffic congestion points at home and abroad, the adaptability of automatic detection methods of traffic events at home and abroad to traffic congestion identification under bridges is analyzed. At the same time, the research on the impact of severe weather on traffic is summarized. Based on this, the research goal, train of thought and technical route are defined. Secondly, by comparing the characteristics of traffic flow data between the normal situation and the day of water accumulation, it is found that the traffic congestion under the bridge will lead to the significantly missing sample size of floating vehicle, and the concept of sample size ratio of floating vehicle data is put forward. At the same time, the concept of sample size ratio of floating vehicle data is put forward. This paper compares and analyzes the similarities and differences of the sample size ratio between traffic congestion and traffic accidents, traffic control, and traffic control. The results show that the missing sample ratio of the West third Ring Expressway in Beijing is nearly 80%, and the missing sample ratio of the West fourth Ring Road Expressway is as high as 97%. Based on the calculation and analysis of the spread and dissipation speed of traffic congestion under the bridge and the vehicle mileage of the congested section, the relationship between the depth of waterlogging under the bridge and the spread of congestion is summarized, and the influence range of congestion space is summarized. Finally, according to the spatial influence range of the traffic congestion under the bridge, the change of speed and the spatial and temporal distribution of the congested section, the sample size ratio is put forward. The identification method of traffic congestion section under bridge with three identification indexes of traffic flow velocity variation and velocity difference is presented, and the program application recognition of congestion point segment based on ArcGIS is realized. Then, considering the traffic flow characteristics of the same day, the traffic flow characteristics are considered synthetically. On the basis of the reduction of traffic capacity under bridge, the ratio of capacity to traffic flow, the entrance and exit of expressway, and the combination of logic judgment and practical experience, At the same time, based on the VISSIM simulation data and floating vehicle data, the parameters of the model are preliminarily calibrated.
【学位授予单位】:北京交通大学
【学位级别】:硕士
【学位授予年份】:2014
【分类号】:U491.265
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