面向交通管理的VANET分布式数据融合

Romain Guyard, V. Berge-Cherfaoui
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引用次数: 0

摘要

在本文中,我们提出了一种分布式融合算法,通过车辆网络中的信息交换来检测交通拥堵。该算法基于对数据和信息源的不确定性进行管理的Dempster-Shafer理论。每辆车都用本地测量数据(速度和间距)和从其他车辆接收到的信息更新数据库,并可以计算自己的路线。通过合作,智能汽车可以避开拥堵的道路,选择更好的路径到达目的地。通过在真实城市道路网络的相扑模拟器上进行的实验,研究了该算法的几种变体,并与集中式方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VANET distributed data fusion for traffic management
In this article, we propose a distributed fusion algorithm to detect traffic congestion through the exchange of messages in vehicle network. This algorithm is based on the Dempster-Shafer theory that manages the uncertainties on data and sources of information. Each vehicle updates its database with local measurements (speed and interdistance) and information received from other vehicles and can calculate its route. Thanks to the collaboration, smart cars can avoid congested roads and take a better path to their destination. Several variants of the algorithm are studied and compared to a centralized approach through experiments carried out on the SUMO simulator using real urban road networks.
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