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RSUs placement using cumulative weight based method for urban and rural roads

机译:基于累积权重的城乡道路RSU放置

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Intelligent Transportation Systems (ITS) deployment became a need nowadays in order to improve quality and efficiency of transportation systems. However, an effective distribution of Roadside Units (RSUs) is considered to be one of the main challenges for deployment of roadside networks, especially due to the wide range of influencing factors that can affect the distribution process. Some of these influencing factors are traffic, topological and infrastructure characteristics of the roads and technology used. This paper introduces the Cumulative Weight based Method (CWM) as a solution to the placement problem in the urban, rural and mountainous areas. The CWM gets the weight of each Site of Interest (SoI) and adds the weights of the surrounding neighbors to its weight and considers the highest weight first in the distribution process. The CWM during the current state of development considers working with the radius of RSUs and connectivity requirements. Moreover, it will be influenced by many other factors. The tests conducted on selected areas in Rostock (Germany) and Spiringen (Switzerland) showed: (1) a reduction in the number of SoIs compared to the original number acquired during the scanning process; (2) only the highest priority SoIs are chosen as the best location for an RSU placement; (3) 3D space calculations for distance on mountainous areas gave a different, more accurate results than 2D space calculations.
机译:如今,为了提高运输系统的质量和效率,智能运输系统(ITS)的部署已成为一种需要。但是,有效分配路边单位(RSU)被认为是部署路边网络的主要挑战之一,特别是由于可能影响分配过程的影响因素范围很广。其中一些影响因素是道路的交通,拓扑和基础设施特征以及所使用的技术。本文介绍了基于累积权重的方法(CWM),以解决城市,农村和山区的安置问题。 CWM获取每个感兴趣站点(SoI)的权重,并将周围邻居的权重与其权重相加,并在分发过程中首先考虑最高权重。在当前的开发状态下,CWM考虑使用RSU的半径和连接性要求。而且,它将受到许多其他因素的影响。在罗斯托克(德国)和斯皮林根(瑞士)的选定区域进行的测试表明:(1)与扫描过程中获取的原始数量相比,SoI数量有所减少; (2)仅选择最高优先级的SoI作为RSU放置的最佳位置; (3)山区距离的3D空间计算得出的结果与2D空间计算结果不同,更准确。

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