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Modeling lane-based traffic flow in emergency situations in the presence of multiple heterogeneous flows.

机译:在存在多个异构流的紧急情况下,对基于车道的交通流进行建模。

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In recent years, natural, man-made and technological disasters have been increasing in magnitude and frequency of occurrence. Terrorist attacks have increased after the September 11, 2001. Some authorities suggest that global warming is partly the blame for the increase in frequency of natural disasters, such as the series of hurricanes in the early-2000's. Furthermore, there has been noticeable growth in population within many metropolitan areas not only in the US but also worldwide. These and other facts motivate the need for better emergency evacuation route planning (EERP) approaches in order to minimize the loss of human lives and property.;This research considers aspects of evacuation routing never before considered in research and, more importantly, in practice. Previous EERP models only either consider unidirectional evacuee flow from the source of a hazard to destinations of safety or unidirectional emergency first responder flow to the hazard source. However, in real-life emergency situations, these heterogeneous, incompatible flows occur simultaneously over a bi-directional capacitated lane-based travel network, especially in unanticipated emergencies. By incompatible, it is meant that the two different flows cannot occupy a given lane and merge or crossing point in the travel network at the same time. In addition, in large-scale evacuations, travel lane normal flow directions can be reversed dynamically to their contraflow directions depending upon the degree of the emergency. These characteristics provide the basis for this investigation. This research considers the multiple flow EERP problem where the network travel lanes can be reconfigured using contraflow lane reversals. The first flow is vehicular flow of evacuees from the source of a hazard to destinations of safety, and the second flow is the emergency first responders to the hazard source.;After presenting a review of the work related to the multiple flow EERP problem, mathematical formulations are proposed for three variations of the EERP problem where the objective for each problem is to identify an evacuation plan (i.e., a flow schedule and network contraflow lane configuration) that minimizes network clearance time. Before the proposed formulations, the evacuation problem that considers only the flow of evacuees out of the network, which is viewed as a maximum flow problem, is formulated as an integer linear program. Then, the first proposed model formulation, which addresses the problem that considers the flow of evacuees under contraflow conditions, is presented. Next, the proposed formulation is expanded to consider the flow of evacuees and responders through the network but under normal flow conditions. Lastly, the two-flow problem of evacuees and responders under contraflow conditions is formulated. Using real-world population and travel network data, the EERP problems are each solved to optimality; however, the time required to solve the problems increases exponentially as the problem grows in size and complexity. Due to the intractable nature of the problems as the size of the network increases, a genetic-based heuristic solution procedure that generates evacuation network configurations of reasonable quality is proposed. The proposed heuristic solution approach generates evacuation plans in the order of minutes, which is desirable in emergency situations and needed to allow for immediate evacuation routing plan dissemination and implementation in the targeted areas.
机译:近年来,自然,人为和技术灾难的发生规模和发生频率在增加。自2001年9月11日以来,恐怖袭击事件有所增加。一些当局认为,全球变暖在一定程度上归咎于自然灾害发生率的增加,例如2000年代初的飓风。此外,不仅在美国,而且在世界范围内,许多大都市地区的人口都有显着增长。这些和其他事实促使人们需要更好的紧急疏散路线规划(EERP)方法,以最大程度地减少人员伤亡和财产损失。;本研究考虑了疏散路线的各个方面,这是研究中从未考虑过的,更重要的是在实践中。以前的EERP模型仅考虑从危险源到安全目的地的单向撤离人员流,或到危险源的单向紧急情况第一响应方流。但是,在现实生活中的紧急情况下,这些异质,不兼容的流量会同时在双向带通行能力的双向行车网络上同时发生,尤其是在意外情况下。不兼容是指两个不同的流不能同时占用给定车道和合并或交叉点。另外,在大规模疏散中,取决于紧急程度,行车道正常流动方向可以动态地反转成其逆流方向。这些特征为这项研究提供了基础。这项研究考虑了多流EERP问题,其中可以使用逆流车道逆转来重新配置网络行驶车道。第一类是从危险源到安全目的地的撤离人员的车辆流,第二类是对危险源的应急第一响应者;在对与多类流EERP问题相关的工作进行了综述之后提出了针对EERP问题的三个变体的公式,其中每个问题的目标是确定一个疏散计划(即,流量计划和网络逆流通道配置),以最大程度地缩短网络清理时间。在提出建议的公式之前,仅考虑撤离人员从网络流出的疏散问题(被视为最大流量问题)被公式化为整数线性程序。然后,提出了第一个提出的模型公式,该模型公式解决了在逆流条件下考虑撤离人员流动的问题。接下来,扩展提议的公式,以考虑在正常流量条件下通过网络的撤离人员和响应者的流量。最后,提出了逆流条件下的疏散与响应者两流问题。利用现实世界中的人口和旅行网络数据,可以将EERP问题分别优化到最佳状态。但是,随着问题的规模和复杂性的增加,解决问题所需的时间呈指数增长。由于问题的棘手性质随着网络规模的增加而提出,提出了一种基于遗传的启发式求解程序,该程序生成质量合理的疏散网络配置。拟议的启发式解决方案方法会在几分钟内生成疏散计划,这在紧急情况下是理想的,并且需要允许在目标区域中立即分发和实施疏散路线计划。

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