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首页> 外文期刊>Internet of Things Journal, IEEE >Vehicle Route Selection Based on Game Evolution in Social Internet of Vehicles
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Vehicle Route Selection Based on Game Evolution in Social Internet of Vehicles

机译:车辆社交网络中基于游戏演化的车辆路径选择

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摘要

Social development and technological advances have enabled the Internet of Vehicles (IoV) to combine the social factors to form a new intelligent transportation system: Social IoV (SIoV). The emergence of SIoV helps to find new traffic management solutions of the serious problems caused by the ever-increasing traffic flow. In this paper, we propose an algorithm called social vehicle route selection (SVRS) to reduce traffic congestion and achieve the purpose of traffic flow control. First, a social clustering method for SIoV is designed by utilizing both historical and current driving information. Then we use game evolution to calculate the optimal route for vehicles, and prove the vehicle route selection game is a potential game and its strategy selection converges to Nash equilibrium. Extensive simulations are carried out to evaluate the SVRS with several performance criteria. Our analysis and simulation results demonstrate that SVRS algorithm can achieve high performance in clustering the vehicles and reducing traffic congestion.
机译:社会发展和技术进步使车辆互联网(IoV)能够将社会因素结合起来,形成一个新的智能交通系统:Social IoV(SIoV)。 SIoV的出现有助于找到新的流量管理解决方案,以解决由不断增加的流量引起的严重问题。在本文中,我们提出了一种称为社交车辆路径选择(SVRS)的算法,以减少交通拥堵并达到交通流量控制的目的。首先,通过利用历史和当前驾驶信息设计用于SIoV的社交聚类方法。然后,利用博弈演化算法计算出车辆的最优路径,证明了车辆路径选择博弈是一种潜在的博弈,其策略选择收敛于纳什均衡。进行了广泛的仿真,以评估具有几种性能标准的SVRS。我们的分析和仿真结果表明,SVRS算法可以在车辆聚集和减少交通拥堵方面实现高性能。

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