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Navigation-Based Traffic Signal Control in Intelligent Transportation Systems

机译:智能交通系统中基于导航的交通信号控制

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摘要

In smart cities, with large numbers of vehicles on roads, including autonomous and manned ones, congestion is still a significant issue and hence smart traffic signal control is indispensable. Nowadays, navigation apps have become increasingly popular and path information is widely available. Due to the development of various vehicular communication technologies, V2X communications become increasingly stable and efficient. Accurate knowledge of traffic flow is key to effective traffic signal control. Most of the existing adaptive strategies rely on video cameras, radars, or other wireless sensors, which involve a huge investment for measuring or estimating real-time flow. In this paper, based on V2I communications, we propose to make use of navigation information of vehicles to obtain real-time traffic flow around each intersection, thus achieving effective traffic signal control. In undersaturated and oversaturated traffic conditions, we analyze the performance of navigation- based strategy to control traffic signal, study how to obtain optimal cycle duration and compare it with the even-distributed fixed-time strategy. Our results can also provide significant insights on other strategies. We conduct extensive simulations to validate our analysis and evaluate the performance of the navigation-based strategy. The results show that the navigation-based strategy is effective and practical, and can further relieve congestion compared with the even-distributed fixed-time strategy.
机译:在智慧城市中,道路上有大量车辆(包括自动驾驶和有人驾驶的车辆),拥堵仍然是一个重要问题,因此,智能交通信号控制是必不可少的。如今,导航应用程序变得越来越流行,并且路径信息已广泛可用。由于各种车辆通信技术的发展,V2X通信变得越来越稳定和高效。准确了解交通流是有效控制交通信号的关键。现有的大多数自适应策略都依赖于摄像机,雷达或其他无线传感器,这需要大量投资来测量或估计实时流量。本文基于V2I通信,提出利用车辆的导航信息获取各路口的实时交通流,从而实现有效的交通信号控制。在饱和和过饱和的交通状况下,我们分析了基于导航的策略来控制交通信号的性能,研究如何获得最佳的循环持续时间,并将其与均匀分布的固定时间策略进行比较。我们的结果还可以为其他策略提供重要见解。我们进行了广泛的仿真,以验证我们的分析并评估基于导航的策略的性能。结果表明,基于导航的策略是有效且实用的,并且与均匀分布的固定时间策略相比,可以进一步缓解拥塞。

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