优先车辆的数据更新模型

A. Shestakov, Yaroslav A. Pletnev, K. A. Frolova
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引用次数: 0

摘要

目前,如何降低信息通信和道路城市基础设施的部署和运营成本是一个非常重要的问题。考虑了现有的考虑移动目标定位的传感器网络消息传递技术,如GGF、GFR、GGR、LAR、ALARM、LACBER等。本文证实了在从外部地理信息系统的主题层更新高度自动化车辆的数据时,需要研究分层网络中减少过度交通的机制。描述了一种使用点对点集群传感器网络的高级过滤程序的方法。提出了一种优先级移动对象分组数据更新算法。作者描述了使用现有的分析和模拟方法来评估提出的改进交通路由程序的可能性,以更新优先车辆在列中移动的空间数据。建议在现有仿真模型的基础上增加一个单元。它考虑了车队中移动的优先交通的具体情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Updating Models for Priority Vehicles
At present, it is quite relevant to search for ways to reduce the cost of deploying and operating infotelecommunication and road urban infrastructure. The existing technologies of message delivery in sensor networks taking into account the positioning of mobile objects are considered, such as GGF, GFR, GGR, LAR, ALARM, LACBER. The paper substantiates the need to study the mechanisms of reducing excessive traffic in hierarchical networks when updating data in highly automated vehicles from the thematic layers of external geoinformation systems. An approach to using advanced filtering procedures for peer-to-peer cluster sensor networks is described. An algorithm for updating data for groups of priority mobile objects is proposed. The authors describe the possibility of using existing analytical and simulation methods to evaluate the proposed improved traffic routing procedures for updating spatial data for priority vehicle that moves in a column. It is proposed to implement an additional unit for the existing simulation model. It takes into account the specifics of priority traffic moving in the convoy.
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