Routing service with real world severe weather

YiRu Li, Sarah George, Craig Apfelbeck, Abdeltawab M. Hendawi, David Hazel, A. Teredesai, Mohamed H. Ali
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引用次数: 14

Abstract

Traditional routing services aim to save driving time by recommending the shortest path, in terms of distance or time, to travel from a start location to a given destination. However, these methods are relatively static and to a certain extent rely on traffic patterns under relatively normal conditions to calculate and recommend an appropriate route. As such, they do not necessarily translate effectively during severe weather events such as tornadoes. In these scenarios, the guiding principal is not, optimize for travel time, but rather, optimize for survivability of the event, i.e., can we recommend an evacuation route to those users inside the hazardous areas. In this demo, we present a framework for routing services for evacuating and avoiding real world severe weather threats that is able to: (1) Identify the users inside the dangerous region of a severe weather event (2) Recommend an evacuation route to guide the users out to a safe destination or shelter (3) Assure the recommended route to be one of the shortest paths after excluding the risky area (4) Maintain the flow of traffic by normalizing the evacuation on the possible safe routes. During the demo, attendees will be able to use the system interactively through its graphical user interface within a number of different scenarios. They will be able to locate the severe weather events on real time basis in any area in USA and examine detailed information about each event, to issue an evacuation query from an existing dangerous area by identifying a destination location and receiving the routing direction on their mobile devices, to issue an avoidance routing query to ask for a shortest path that avoids the dangerous region, to have an inside look into the internal system components and finally, to evaluate the overall system performance.
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具有真实世界恶劣天气的路由服务
传统的路线服务旨在通过推荐从起点到给定目的地的最短路径(从距离或时间来看)来节省驾驶时间。然而,这些方法都是相对静态的,在一定程度上依赖于相对正常情况下的交通模式来计算和推荐合适的路线。因此,在龙卷风等恶劣天气事件中,它们不一定有效地转化。在这些场景中,指导原则不是优化出行时间,而是优化事件的生存能力,即我们能否向危险区域内的用户推荐一条疏散路线。在这个演示中,我们提出一个框架路由服务撤离,避免现实世界能恶劣天气威胁:(1)确定用户在危险地区的恶劣天气事件(2)推荐一个疏散路线引导用户去一个安全的目的地或住所(3)保证推荐的路线的最短路径排除危险区域(4)维护交通流的正常化可能安全的疏散路线。在演示期间,与会者将能够在许多不同的场景中通过其图形用户界面交互式地使用该系统。他们将能够实时定位美国任何地区的恶劣天气事件,并检查每个事件的详细信息,通过确定目的地位置并在移动设备上接收路由方向,从现有的危险区域发出疏散查询,发出避免路由查询,请求避开危险区域的最短路径,内部查看内部系统组件,最后,评估系统的整体性能。
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