Model-based assessment of the impact of driver-assist vehicles using kinetic theory
Model-based assessment of the impact of driver-assist vehicles using kinetic theory
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DOI：
10.1007/s00033-020-01383-9
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发表时间：
2020-08-27
影响因子：
2
通讯作者：
Zanella, Mattia
中科院分区：
文献类型：
--
作者：
Piccoli, Benedetto;Tosin, Andrea;Zanella, Mattia
在本文中，我们考虑了跟随领导者交通模型的动力学描述，我们用它来研究不同规模的车辆驾驶辅助控制策略的效果，从局部交通到宏观车辆流。我们提供的理论证据表明，一些典型的控制策略，例如速度的调整和车头时距的优化，会影响当地的交通特征（例如，导致当地交通不稳定的速度和车头时距离散），但对可观察的宏观交通趋势（例如，车辆的流量/吞吐量）几乎没有影响。这一不明显的结论与最近对自动驾驶汽车的实地研究非常吻合，表明动力学方法可能是有机多尺度研究以及驾驶员辅助算法设计的有效工具。
In this paper, we consider a kinetic description of follow-the-leader traffic models, which we use to study the effect of vehicle-wise driver-assist control strategies at various scales, from that of the local traffic up to that of the macroscopic stream of vehicles. We provide theoretical evidence of the fact that some typical control strategies, such as the alignment of the speeds and the optimisation of the time headways, impact on the local traffic features (for instance, the speed and headway dispersion responsible for local traffic instabilities) but have virtually no effect on the observable macroscopic traffic trends (for instance, the flux/throughput of vehicles). This unobvious conclusion, which is in very nice agreement with recent field studies on autonomous vehicles, suggests that the kinetic approach may be a valid tool for an organic multiscale investigation and possibly the design of driver-assist algorithms.