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首页> 外文会议>2012 IEEE International Conference on Vehicular Electronics and Safety >Analytical modeling of vehicle-to-vehicle communication using spread of infection models
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Analytical modeling of vehicle-to-vehicle communication using spread of infection models

机译：使用传播模型传播的车对车通信的分析模型

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摘要

In this study we propose a macroscopic analytical model for modeling the vehicle-to-vehicle (V2V) communication process. Real-time information propagation by V2V communication is part of the Vehicle Infrastructure Integration (VII) initiative, aimed at improving the traffic conditions on existing roadways. Vehicles communicate among themselves and pass information regarding congestion, unsafe pavement condition or accidents. This proposed information propagation model is based on the Susceptible-Infected-Removed (SIR) model that is used to model the spread of epidemics in a region. As an analogy, we call the vehicles that have received the signal as ‘infected vehicles’, and those instrumented vehicles that have not received the information are called ‘susceptible vehicles’. The proposed model predicts the number of infected vehicles present on the roadway at every instant of time. The model is developed for a variety of traffic conditions including different volumes, market share of instrumented vehicles, speed limits and number of lanes. Finally, it is validated using simulation results obtained from Paramics, traffic micro-simulation software.
机译：在这项研究中，我们提出了一种宏观分析模型，用于对车辆到车辆（V2V）的通信过程进行建模。通过V2V通信进行实时信息传播是“车辆基础设施集成（VII）”计划的一部分，该计划旨在改善现有道路的交通状况。车辆之间进行通信并传递有关拥堵，不安全的路面状况或事故的信息。该提议的信息传播模型基于易感性感染去除（SIR）模型，该模型用于对区域内流行病的传播进行建模。打个比方，我们将收到信号的车辆称为“感染车辆”，而未接收到该信息的仪表车辆称为“易感车辆”。提出的模型可预测每个时刻在道路上存在的被感染车辆的数量。该模型是针对各种交通状况而开发的，包括不同的数量，仪表车辆的市场份额，速度限制和车道数量。最后，使用从交通模拟软件Paramics获得的模拟结果对其进行验证。

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