Towards the Optimization of Road Side Unit Placement Using Genetic Algorithm

Mahmoud Al Shareeda, Ayman Khalil, W. Fahs
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引用次数: 22

Abstract

The most significant elements of a vehicular ad hoc network (VANET), besides VANET-enabled vehicles, are roadside units (RSUs). The effectiveness of a VANET mainly depends on the density and location of these RSUs. Throughout the primary stages of VANET, it will not be potential to deploy a big number of RSUs either due to the low marketplace penetration of VANET enabled vehicles or due to the deployment price of RSUs. There is, therefore, a need to optimally place a limited number of RSUs in a specified area in order to accomplish maximum performance. In this paper, we present the well-known genetic algorithm based on RSU location to find an optimal or near optimal solution. We provide the basic simulation environment of this work OSM to download real map data, GatcomSUMO to generate car mobility, SUMO to simulate road traffic, veins model framework for running vehicular network simulations on Omnet++, Omnet++ to simulate realistic network and Matlab to build the algorithm in order to analyze the results. The simulation scenario is based on the Hamra district of Beirut, Lebanon. Based on the genetic algorithm, our proposed RSU placement model demonstrates that an optimal RSU position that can enhance the reception of basic safety message (BSM) delivered from the vehicles, can be accomplished in a specified road-map layout.
基于遗传算法的路边单元布局优化研究
除了支持VANET的车辆外,车辆自组织网络(VANET)中最重要的元素是路边单元(rsu)。VANET的有效性主要取决于这些rsu的密度和位置。在VANET的初级阶段,由于支持VANET的车辆的市场渗透率较低,或者由于rsu的部署价格,部署大量rsu的可能性不大。因此,需要在指定区域最佳地放置有限数量的rsu,以实现最大性能。在本文中,我们提出了一种著名的基于RSU定位的遗传算法来寻找最优或近最优解。我们提供了本工作的基础仿真环境OSM下载真实地图数据,GatcomSUMO生成汽车机动性,SUMO模拟道路交通,在omnet++上运行车辆网络仿真的脉络模型框架,omnet++模拟现实网络,Matlab构建算法并对结果进行分析。模拟场景以黎巴嫩贝鲁特的哈姆拉地区为基础。基于遗传算法,我们提出的RSU位置模型表明,在指定的路线图布局中,可以实现最优的RSU位置,以增强车辆传递的基本安全信息(BSM)的接收。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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