高速公路常态性雾区行车智能诱导策略研究

发布时间：2018-07-16 21:42

【摘要】：雾长期以来一直是影响高速公路运营安全与效率的重要因素之一,尤其是当前经济发展的背景下,雾、霾天气频发,其影响范围增广,防范难度随之加大,大雾天气诱发的多车连环追尾事故早已屡见不鲜。论文以贵州省交通运输厅科技项目—仁赤高速公路交通安全保障关键问题研究与示范应用(合同编号GZSGLJKYWT-2013-01)为依托,在大量查阅国内外有关雾天交通安全的文献基础上,通过分析高速公路雾区车辆运行特征与事故特征,以交通流理论为基础建立了自适应神经网络模型,并得到高速公路雾区速度、车距控制策略,据此对雾区智能诱导系统的参数设置进行研究,具体工作如下:首先,论文利用国内外大量研究成果从宏观和微观两个层面分析了雾区路段交通运行状况,以交通流理论为工具,从宏观的角度分析得出保障车流安全、顺畅运行效率的控制方程,再以此为契机,深入到微观层面,以车速、车距为控制目标,结合前人已有的研究成果寻求控制雾区路段车辆安全顺畅运行的微观约束方程;其次,根据微观约束方程获取准则数据对,并以此作为自适应神经网络的训练数据,利用MATLAB建立雾天车速控制的自适应神经网络模型,并利用准则数据对模型进行有效性检验,应用模型对微观约束方程加以论证,说明其合理性并提出一定能见度、交通量、路面湿滑状况下的车速、车距控制策略,结合vissim仿真获取虚拟状态下的行程时间进行分析,说明速度诱导策略的有效性;再次,阐明雾区智能诱导系统的概念、基本框架、功能结构等,根据车距控制策略制定系统的控制策略,车速控制策略则作为信息发布系统的输出内容,以诱导系统与信息发布系统两者为技术策略从视觉上诱导驾驶员控制车辆安全行驶,并介绍系统在实际工程中的应用与效果,说明其对保障常态性雾区交通安全所起的积极作用;最后,建立高速公路雾区交通安全分级评价指标体系,研究高速公路雾区安全性分级评价方法,用以评估策略的应用效果,诱导管理者采取不同等级的应对方案,通过实例对比分析说明评价方法可靠;介绍了雾区交通安全的管控对策。论文建立的自适应神经网络模型可植入雾区智能诱导系统,方便车辆的自适应控制,也为后续研究奠定了理论基础;所提出的低能见度下的车速、车距控制策略使得雾天高速公路机械式管控轻重有别、缓急有序、愈加灵活合理。雾区智能诱导系统适用于高速公路大雾频发的路段,为解决雾区交通安全保障问题提供了新的思路与方法,对高速公路的交通安全与畅通具有积极的作用。
[Abstract]:Fog has long been one of the important factors that affect the safety and efficiency of expressway operation. Especially under the background of current economic development, fog and haze weather occur frequently, and the influence range increases and the prevention difficulty increases. Heavy fog weather induced multiple car chain tail accident has long been common. Based on the research and demonstration application of the key problems of traffic safety and security of Renchi Expressway (contract No. GZSGLJKYWT-2013-01), the thesis is based on the scientific and technological project of Guizhou Provincial Traffic and Transportation Department, and on the basis of consulting a large number of documents on traffic safety in foggy days at home and abroad. Based on the traffic flow theory, an adaptive neural network model is established by analyzing the characteristics of vehicle operation and accident in the fog zone of expressway, and the control strategy of speed and distance between vehicles in the fog zone of expressway is obtained. According to this, the parameter setting of intelligent guidance system in fog area is studied. The specific work is as follows: firstly, the paper analyzes the traffic condition of fog zone from macro and micro aspects by using a large number of research results at home and abroad. With traffic flow theory as a tool, the control equation of ensuring the safety and smooth running efficiency of traffic flow is obtained from the macroscopic angle, and then it is taken as an opportunity to go deep into the micro level and take the speed and distance as the control target. Combined with the previous research results, we seek the microscopic constraint equation to control the safe and smooth operation of vehicles in fog zone. Secondly, we obtain the criterion data pair according to the microscopic constraint equation, and take it as the training data of adaptive neural network. The adaptive neural network model of speed control in fog weather is established by MATLAB, and the validity of the model is tested by the criterion data. The microscopic constraint equation is proved by the model, and the rationality of the model is proved, and the visibility and traffic volume are given. The speed and distance control strategy under the condition of wet slippery road surface, combined with vissim simulation to obtain the travel time under the virtual state are analyzed to illustrate the effectiveness of the speed guidance strategy. Thirdly, the concept and basic framework of the intelligent guidance system in fog zone are expounded. Function structure and so on, according to the vehicle distance control strategy to formulate the system control strategy, the speed control strategy is used as the information release system output content, In this paper, the guidance system and the information publishing system are taken as the technical strategies to guide the driver to control the safe driving of the vehicle visually, and the application and effect of the system in the practical engineering are introduced. It shows that it plays an active role in ensuring the traffic safety in the normal fog area. Finally, the index system of traffic safety grading in the fog zone of expressway is established, and the evaluation method of the safety grade in the fog zone of expressway is studied to evaluate the application effect of the strategy. This paper induces managers to adopt different levels of coping schemes, and shows that the evaluation method is reliable through the comparative analysis of examples, and introduces the control measures of traffic safety in fog area. The adaptive neural network model established in this paper can be implanted into the intelligent guidance system of fog zone, which is convenient for the adaptive control of vehicles and lays a theoretical foundation for further research. The distance control strategy makes the mechanical control of foggy expressway more flexible and reasonable. The intelligent guidance system of fog zone is suitable for the section of expressway with frequent fog, which provides a new way of thinking and method to solve the problem of traffic safety in fog area, and plays an active role in the traffic safety and smooth of expressway.
【学位授予单位】：重庆交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495

【二级参考文献】