复杂通信场景下的排控算法评估平台

Sijie Zhu, Dip Goswami, Hong Li
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引用次数: 2

摘要

协作式自适应巡航控制(CACC)扩展了自适应巡航控制技术,在欧洲5.9 GHz频段(ITS-G5)的自组织网络中,通过车辆对一切(V2X)通信进行车辆之间的额外信息交换。利用V2X提供的超视距信息,排控算法实现了更短的安全车际距离。然而,无线通信的不完善可能会影响排的性能(例如,允许的车际距离)。具体来说,在拥挤的交通场景中,基于拥塞水平(传输速率控制(TRC))来调节消息速率的分散式拥塞控制方法可能会显著降低队列性能。在这项工作中,我们提出了一个基于ITS-G5通道中运行的工业V2X节点的排控制算法评估平台。采用纵向车辆动力学模型对实车进行仿真。模型在环测试结果表明,当消息速率受到TRC的限制和降低时,CACC的性能明显下降。我们的评估结果进一步得出结论,现有标准施加的这种复杂通信场景的影响应该在未来的排控制算法中明确建模。
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Evaluation Platform of Platoon Control Algorithms in Complex Communication Scenarios
Cooperative Adaptive Cruise Control (CACC) extends the Adaptive Cruise Control technology with additional information exchange between vehicles over vehicle-to-everything (V2X) communications in an ad-hoc network at 5.9 GHz band (ITS-G5) in Europe. Using beyond line-of-sight information provided by V2X, the platoon control algorithms realize a shorter safe inter-vehicle distance. Nevertheless, the platoon performance (e.g., the allowable inter-vehicle distance) may be impacted by the imperfectness of wireless communications. Specifically, in congested traffic scenarios, a Decentralized Congestion Control method that regulates message rate based on congestion level (Transmit Rate Control (TRC)), may significantly reduce the platoon performance. In this work, we propose an evaluation platform for platoon control algorithms based on industrial V2X nodes operating in the ITS-G5 channels. The real car is simulated by a longitudinal vehicle dynamic model. The model-in-the-loop test results demonstrate that the performance of CACC goes down significantly when the message rate is restricted and reduced by TRC. Our evaluation results further conclude that the effect of such complex communication scenarios imposed by the existing standards should be explicitly modelled in the future platoon control algorithms.
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