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Novel and Automated Methodology to Model and Analyze Massive Evacuation along the Highway System.

机译：新型自动化方法，可对公路系统的大规模疏散进行建模和分析。

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摘要

Unpredictable natural disasters or terrorist attacks may require that the residents of the attacked area be evacuated immediately using a partially damaged infrastructure. Evacuees may not have access to working vehicles, and may need to walk to the closest shelter or to a temporary safe place where public transit such as buses will pick them up. A portion of the population will get injured and have to go to hospitals.;An automatic process of assigning addresses to the closest hospital, shelter or safe place based on shortest distance along a potentially damaged road system has been developed. Alternatively, people with access to vehicles are assigned to exit locations on the county borders. The graph-theoretic Voronoi Diagram (GTVD) can be computed efficiently and in real time using our data structures. Guilford County data was used as an example where public schools are assumed to be the safe places. We found that the assignment was not uniform at all, and some underutilized safe places were therefore discounted, and the assignment was redone. Moreover, we create data structures that are automatically derived from Geographic Information Systems (GIS) shapefiles. The data structures emphasize the computational geometric-aspect.;A model of the highway system described in our data structure has been used to automatically develop a colored deterministic and stochastic Petri net which can then be used to simulate the dynamics of people movement on the highway system towards medical facility or exit or safe points. The basic idea behind the model is that an intersection will be a subnetwork of several queues. For example a full bidirectional 4-way stop sign intersection can be represented by nine servers whose service time is either exponential or deterministic. The intersection will serve the vehicles from the incoming traffic flow and move each vehicle to its target road segment that connects to the next intersection on the path of its destination.;We introduce a modeling procedure based on Petri nets for road intersections where each intersection consists of several places and several transitions. We introduce the concepts of places denoted as intersection-Hold (I-Hold), Fusion, Branching and road-Hold (R-Hold) places. Vehicles at an I-Hold place are inside the intersection. In a Fusion place, vehicles are waiting to enter the intersection. In the Branching place, vehicles are leaving the intersection and are assigned to their next road segments. In R-Hold place, vehilces are on the road segment. Entering the intersection is controlled by a deterministic transition that represents the arrival rate to the intersection. Leaving the intersection is controlled by a stochastic transition which is the service rate for the intersection. Similarly, entering the road segment is controlled by a deterministic transition that represents the arrival rate to the road segment and leaving the road segment is controlled by a deterministic transition which is the service rate. For example the 4-way stop sign intersection has 11 places (8 R-Hold, 1 Fusion, 1 Branching, 1 I-Hold) and 18 transitions.;We develop a mesoscopic modeling and simulation approach for modeling traffic flow over a large geographic area where people at addresses are assigned to vehicles and their destinations and routes are computed. To make the simulation specific, we consider the scenario in which most people self-evacuate GC through the closest exit points over the shortest path. Dijkstra's algorithm is used to compute the shortest paths. The simulation approach is microscopic in the sense that individual vehicles are simulated but that the highway system and the vehicle interactions are simplified.;We develop an automatic method to assemble the Petri net that represents the evacuation of Guilford County (GC). The Petri net includes 35476 places, 43540 transitions with 531595 tokens where each token represents a single person in GC. We simulate the evacuation and develop statistics and evaluation for the results. We found that the evacuation took about 8.7 hours. We locate the bottlenecks of the evacuation.
机译：不可预测的自然灾害或恐怖袭击可能要求立即使用部分受损的基础设施撤离受灾地区的居民。疏散人员可能无法使用工作车辆，并且可能需要步行到最近的避难所或临时安全的地方，例如公交车将把他们接走。一部分人口将受伤并必须去医院。已开发出一种自动过程，可以根据沿潜在损坏的道路系统的最短距离，将地址分配给最近的医院，庇护所或安全场所。另外，可以将有车辆通行的人员分配到县境的出口地点。使用我们的数据结构可以有效地实时计算图论Voronoi图（GTVD）。以吉尔福德县的数据为例，假定公立学校是安全的地方。我们发现分配工作根本不是统一的，因此一些未充分利用的安全场所被打折了，重新分配了工作。此外，我们创建了从地理信息系统（GIS）shapefile自动派生的数据结构。数据结构着重于计算的几何方面。我们数据结构中描述的高速公路系统模型已用于自动开发彩色确定性和随机Petri网，然后可用于模拟高速公路上人员移动的动态朝向医疗设施或出口或安全点的系统。该模型背后的基本思想是，交叉路口将是多个队列的子网。例如，一个完整的双向4路停车标志交叉路口可以由九台服务器表示，它们的服务时间是指数或确定性的。交叉路口将根据传入的交通流为车辆提供服务，并将每辆车移动到其目标道路段，该目标路段连接到目的地路径上的下一个交叉路口。几个地方和几个过渡。我们介绍了表示为交叉点保留（I-Hold），融合，分支和道路保留（R-Hold）地点的概念。 I-Hold处的车辆在十字路口内。在融合地区，车辆正在等待进入十字路口。在“分支”位置，车辆将离开交叉路口并分配给其下一个路段。在R-Hold地点，车辆在路段上。进入交叉路口由确定性过渡控制，该过渡表示到达交叉路口的速度。离开十字路口由随机过渡控制，随机过渡是十字路口的服务费率。类似地，进入道路段由确定性过渡控制，该过渡表示到达道路段的到达率，而离开道路段则由确定性过渡控制，即服务率。例如，四向停车标志交叉路口有11个位置（8个R保持，1个融合，1个分支，1个I保持）和18个过渡。;我们开发了一种介观的建模和仿真方法来对大型地理区域的交通流进行建模将地址中的人员分配到车辆并计算其目的地和路线的区域。为了使仿真更具体，我们考虑了大多数人通过最短路径上最近的出口点对GC进行自动撤离的情况。 Dijkstra的算法用于计算最短路径。在模拟单个车辆但简化公路系统和车辆交互的意义上，该模拟方法是微观的。我们开发了一种自动方法来组装表示吉尔福德县（GC）疏散的Petri网。 Petri网包含35476个位置，带有535595个令牌的43540个转换，其中每个令牌代表GC中的一个人。我们模拟疏散情况，并对结果进行统计和评估。我们发现疏散时间约8.7个小时。我们找到了疏散的瓶颈。

著录项

  • 作者

    Qabaja, Hamzeh.;

  • 作者单位

    North Carolina Agricultural and Technical State University.;

  • 授予单位 North Carolina Agricultural and Technical State University.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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