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Efficient Path Routing Over Road Networks in the Presence of Ad-Hoc Obstacles

机译:存在Ad-Hoc障碍物的道路网络上的高效路径路由

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Nowadays, the path routing over road networks has become increasingly important, yet challenging, in many real-world applications such as location-based services (LBS), logistics and supply chain management, transportation systems, map utilities, and so on. While many prior works aimed to find a path between a source and a destination with the smallest traveling distance/time, they do not take into account the quality constraints (e.g., obstacles) of the returned paths, such as uneven roads, roads under construction, and weather conditions on roads. Inspired by this, in this paper, we consider two types of ad-hoc obstacles, keyword-based and weather-based obstacles, on road networks, which can be used for modeling roads that the returned paths should not pass through. In the presence of such ad-hoc obstacles on roads, we formulate a path routing query over road networks with ad-hoc obstacles (PRAO), which retrieves paths from source to destination on road networks that do not pass ad-hoc keyword and weather obstacles and have the smallest traveling time. In order to efficiently answer PRAO queries, we design effective pruning methods and indexing mechanism to facilitate efficient PRAO query answering. Extensive experiments have demonstrated the efficiency and effectiveness of our approaches over real/synthetic data sets. (C) 2019 Elsevier Ltd. All rights reserved.
机译:如今,在许多实际应用中,例如基于位置的服务(LBS),物流和供应链管理,运输系统,地图实用程序等,道路网络上的路径路由变得越来越重要,但也充满挑战。尽管许多先前的工作旨在找到源与目的地之间具有最小行驶距离/时间的路径,但它们并未考虑返回路径的质量约束(例如,障碍物),例如不平坦的道路,在建的道路以及道路上的天气情况。受此启发,在本文中,我们考虑了道路网络上的两种特殊障碍,基于关键字的障碍和基于天气的障碍,可用于对返回的路径不应该经过的道路进行建模。在道路上存在此类临时障碍的情况下,我们在具有临时障碍的道路网络(PRAO)上制定路径路由查询,该查询可检索未通过临时关键字和天气的道路网络上从源到目的地的路径障碍物并具有最小的行驶时间。为了有效回答PRAO查询,我们设计了有效的修剪方法和索引机制来促进PRAO查询的有效回答。大量的实验证明了我们的方法在实际/综合数据集上的效率和有效性。 (C)2019 Elsevier Ltd.保留所有权利。

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