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Assessment of connected vehicle information quality for signalised traffic control

机译:用于信号交通控制的连接车辆信息质量评估

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Connected vehicles (CVs) present a great opportunity to smooth and improve traffic flows at intersections thanks to their communication capabilities, which may allow a real-time flow of information with the controllers operating traffic signals. Therefore, it is reasonable to envision that, in the near future, CV data may complement or replace spot detector data that is currently used to operate traffic signals. However, CV data may be affected by errors, such as positioning error, which may depend on the technology that is employed for collecting such information. In this paper, we investigate the performances of different control strategies, namely a strategy that employs only aggregated information, such as queue lengths, and a strategy using disaggregated vehicle-based information, when they are operated with CV data, considering various realistic measurement accuracy settings. Our experiments, conducted via microscopic simulations, show that the disaggregated strategy features better performance and robustness in most of the tested scenarios.
机译:互联车辆(CV)由于其通信能力,为平顺和改善交叉口的交通流提供了一个很好的机会,这可能允许与控制交通信号的控制器进行实时信息流。因此,可以合理设想,在不久的将来,CV数据可能会补充或取代目前用于操作交通信号的spot探测器数据。然而,CV数据可能会受到误差的影响,例如定位误差,这可能取决于用于收集此类信息的技术。在本文中,我们研究了不同控制策略的性能,即仅使用聚合信息(如队列长度)的策略,以及使用基于车辆的分类信息的策略,在使用CV数据时,考虑到各种实际测量精度设置。我们通过微观模拟进行的实验表明,在大多数测试场景中,分类策略具有更好的性能和鲁棒性。

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