In this paper, we derive second order hydrodynamic traffic models from kinetic-controlled equations for driver-assist vehicles. At the vehicle level we take into account two main control strategies synthesising the action of adaptive cruise controls and cooperative adaptive cruise controls. The resulting macroscopic dynamics fulfil the anisotropy condition introduced in the celebrated Aw-Rascle-Zhang model. Unlike other models based on heuristic arguments, our approach unveils the main physical aspects behind frequently used hydrodynamic traffic models and justifies the structure of the resulting macroscopic equations incorporating driver-assist vehicles. Numerical insights show that the presence of driver-assist vehicles produces an aggregate homogenisation of the mean flow speed, which may also be steered towards a suitable desired speed in such a way that optimal flows and traffic stabilisation are reached.
翻译:在本论文中,我们从驾驶辅助车辆动能控制方程式中得出第二顺序流体动力交通模型。在车辆一级,我们考虑到综合适应性巡航控制和合作性适应性巡航控制行动的两项主要控制战略。由此产生的宏观动态符合著名的Aw-Rascle-Zhang模型中引入的厌食状态。与其他基于休眠论的模型不同的是,我们的方法揭示了经常使用的流体动力交通模型背后的主要物理方面,并说明了由此形成的包含驾驶辅助车辆的宏观方程式的结构。数字见解显示,驾驶辅助车辆的存在产生了平均流动速度的总体同质化,这也可能被引向一个合适的理想速度,以便达到最佳流动和交通稳定。