In this paper, we propose a kinetic model of traffic flow with uncertain binary interactions, which explains the scattering of the fundamental diagram in terms of the macroscopic variability of aggregate quantities, such as the mean speed and the flux of the vehicles, produced by the microscopic uncertainty. Moreover, we design control strategies at the level of the microscopic interactions among the vehicles, by which we prove that it is possible to dampen the propagation of such an uncertainty across the scales. Our analytical and numerical results suggest that the aggregate traffic flow may be made more ordered, hence predictable, by implementing such control protocols in driver-assist vehicles. Remarkably, they also provide a precise relationship between a measure of the macroscopic damping of the uncertainty and the penetration rate of the driver-assist technology in the traffic stream.

中文翻译：

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驾驶员辅助控制在动态交通模型中的不确定性阻尼

在本文中，我们提出了一种具有不确定二元相互作用的交通流动力学模型，该模型根据由车辆产生的平均速度和车辆通量等总量的宏观变化来解释基本图的散射。微观不确定性。此外，我们在车辆之间的微观相互作用层面设计了控制策略，通过这种策略，我们证明可以抑制这种不确定性在各个尺度上的传播。我们的分析和数值结果表明，通过在驾驶员辅助车辆中实施此类控制协议，可以使总交通流量更加有序，从而可预测。值得注意的是，