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Techniques for efficient road-network-based tracking of moving objects

机译:基于路网的有效运动对象跟踪技术

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摘要

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. A setting is assumed in which a central database stores a representation of each moving object's current position. This position is to be maintained so that it deviates from the user's real position by at most a given threshold. To do so, each moving object stores locally the central representation of its position. Then, an object updates the database whenever the deviation between its actual position (as obtained from a GPS device) and the database position exceeds the threshold. The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and, it proposes to use acceleration profiles together with the routes. Using real GPS-data and a corresponding real road network, the paper offers empirical evaluations and comparisons that include three existing approaches and all the proposed approaches.
机译:随着无线通信,地理定位和消费类电子产品的不断发展,正在出现一种基础设施,该基础设施使基于位置的服务能够依赖于跟踪称为服务对象的整个服务用户群体不断变化的位置。这种情况的特点是大量更新,因此,位置更新技术变得很重要。假设设置是在其中中央数据库存储每个运动对象的当前位置的表示形式。该位置将被保持,以至于它偏离用户的真实位置至多给定阈值。为此,每个移动对象都在本地存储其位置的中心表示。然后,只要对象的实际位置(从GPS设备获取)与数据库位置之间的偏差超过阈值,就会更新数据库。考虑的主要问题是如何在数据库中表示运动对象的位置,以便可以使用尽可能少的更新来进行跟踪。本文建议使用假设对象在其中移动的道路网络来预测其未来位置。本文提出了修改初始路网表示的算法,以便更好地用作预测对象位置的基础。它建议以路线的形式使用物体的已知运动模式;并且建议将加速曲线与路线一起使用。利用真实的GPS数据和相应的真实道路网络,本文提供了经验评估和比较,包括三种现有方法和所有提出的方法。

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