首页> 外文会议>Local Computer Networks, 2009. LCN 2009 >Stochastic traffic and connectivity dynamics for vehicular ad-hoc networks in signalized road systems
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Stochastic traffic and connectivity dynamics for vehicular ad-hoc networks in signalized road systems

机译:信号化道路系统中车辆自组织网络的随机交通和连通性动态

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In the design and planning of vehicular ad-hoc networks, road-side infrastructure nodes are commonly used to improve the overall connectivity and communication capability of the networks, however, to determine the locations to install the infrastructure nodes for optimal performance based on the ever-changing density and connectivity dynamics of moving vehicles remains to be a challenging issue. In this paper, we introduce a stochastic traffic model to capture the space and time dynamics of vehicles in signalized urban road systems to identify poorly-connected regions for infrastructure node placements. To closely approximate the practical road conditions, we propose a density-dependent velocity profile to approximate vehicle interactions and capture platoons formation and dissipation at traffic signals. Numerical results are presented to evaluate the stochastic traffic model. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the understandings of the vehicular density dynamics from the proposed model, we illustrate that connectivity dynamics of vehicles can be determined and consequent system engineering and planning can be carried out.
机译:在车辆自组织网络的设计和规划中,通常使用路侧基础设施节点来改善网络的整体连接性和通信能力,但是,基于以往的经验,可以确定安装基础设施节点的位置以获得最佳性能。改变行驶中车辆的密度和连通性仍然是一个具有挑战性的问题。在本文中,我们引入了一种随机交通模型,以捕获信号化城市道路系统中车辆的时空动态,以识别基础设施节点放置位置较差的区域。为了紧密逼近实际道路状况,我们提出了一种依赖于密度的速度曲线,以近似车辆的相互作用并捕获交通信号线的排的形成和消散。数值结果被提出来评估随机交通模型。总的来说,我们显示出流体模型可以充分描述交通流的平均行为,而随机模型可以很好地近似概率分布,即使车辆在交通信号灯控制下彼此互动时也是如此。通过对所提出模型的车辆密度动力学的理解,我们说明了可以确定车辆的连通性动力学,从而可以进行系统工程和计划。

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