不同天气情况下的高速公路交通流特性研究

发布时间：2018-06-10 02:37

本文选题：高速公路 + 不同天气情况　；参考：《哈尔滨工业大学》2014年硕士论文

【摘要】：近些年来，特殊不良天气发生次数越来越多，加上机动车保有量持续增长，交通拥挤和交通事故等现象频繁发生，严重影响了城市社会经济生活和高速公路交通运行。为了缓解这些交通问题，交通流的运行特性、分布特性以及相互关系成为重要研究对象。但是，目前对交通流特性研究还不太全面深入，已有的交通流参数模型大部分是基于经典交通流三参数进行研究，而没有仔细探讨其他交通流参数之间的关系。不良天气条件下的交通管理措施一般是根据以往经验，人工制定和调整，缺乏科学的理论指导以及交通流理论的支撑，使得交通系统在特殊天气下极易造成瘫痪。因此，要降低不良天气对高速公路交通系统运行的影响，制定合理的交通管理措施与控制策略，必须要掌握各种不利天气条件下的交通流参数变化规律。本文首先探讨了交通流研究中的实测现象，比较了环形线圈检测技术、视频检测技术、无线定位技术等几种交通流实测方法，确定使用视频检测技术来获取研究所需要的交通流数据。其次对视频数据的采集方案（例如采集工具、采集时间、采集地点等）进行了详细的说明。阐述了视频数据检测的应用原理，并通过视频检测程序和技术后处理得到了交通流的各种参数数据。另外重点分析了交通流研究方法和高速公路基本路段的交通流运行特征。然后以正常、降雨及降雪天气条件下高速公路基本路段交通流作为研究对象，根据不利天气条件影响下的交通流特征参数选取原则，选取了速度、速度差、加速度、车头时距、侧向偏移等特征参数。通过对不同天气条件下的交通流参数的概率分布特性、显著差异性进行分析，获得降雨和降雪条件对高速公路微观交通流参数的衰减程度。结合以上分析，运用面域分布模型、曲线拟合和回归分析等数学方法，建立了各种不同天气条件下的交通流参数相互关系模型，最后通过实际观测数据解释了模型的有效性与合理性，丰富了高速公路微观交通流规律，能够为高速公路交通管理与控制提供一定的理论基础与实践价值。
[Abstract]:In recent years, the frequency of special bad weather is more and more, along with the continuous increase of vehicle ownership, traffic congestion and traffic accidents, which seriously affect the urban social and economic life and highway traffic operation. In order to alleviate these traffic problems, traffic flow characteristics, distribution characteristics and interrelationships have become an important research object. However, at present, the research on traffic flow characteristics is not very thorough. Most of the existing traffic flow parameter models are based on the classical three parameters of traffic flow, and the relationship between other traffic flow parameters is not discussed carefully. Traffic management measures under bad weather conditions are usually based on past experience, manual formulation and adjustment, lack of scientific theoretical guidance and the support of traffic flow theory, which makes traffic system easily paralyzed in special weather. Therefore, in order to reduce the impact of bad weather on the operation of expressway traffic system, we should formulate reasonable traffic management measures and control strategies. It is necessary to master the variation law of traffic flow parameters under various adverse weather conditions. Firstly, this paper discusses the measured phenomena in traffic flow research, and compares the ring coil detection technology and video detection technology. Several traffic flow measurement methods, such as wireless location technology, are used to obtain the traffic flow data needed by the research. Secondly, the video data acquisition scheme (such as acquisition tools, acquisition time, collection location and so on) is described in detail. This paper describes the application principle of video data detection, and obtains all kinds of traffic flow parameter data by video detection program and post-processing technology. In addition, the research methods of traffic flow and the characteristics of the traffic flow in the basic section of the expressway are analyzed. Then, the traffic flow of the basic section of the highway under normal, rainfall and snowfall weather conditions is taken as the research object. According to the principle of selecting characteristic parameters of traffic flow under adverse weather conditions, the characteristic parameters such as velocity, velocity difference, acceleration, headway time distance, lateral deviation and so on are selected. By analyzing the probability distribution characteristics of traffic flow parameters under different weather conditions, the significant differences are analyzed, and the attenuation degree of traffic flow parameters of freeway under rainfall and snow conditions is obtained. Combined with the above analysis, using the area distribution model, curve fitting and regression analysis, the relationship model of traffic flow parameters under different weather conditions is established. Finally, the validity and rationality of the model are explained through actual observation data, which enriches the microscopic traffic flow law of expressway, and can provide a certain theoretical basis and practical value for expressway traffic management and control.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.112

【参考文献】