用于网络上交通流模拟的易用算法：数值实验
An easy-to-use algorithm for simulating traffic flow on networks: numerical experiments
AI总结：
本文提出一种基于Godunov的离散化方法，用于模拟网络上的车辆流，该方法自动选择可行解，无需额外步骤，实现简便。
摘要：
本文提出了一种基于Godunov的超几何守恒律离散化方法，用于建模网络上的车辆流。每个方程描述沿网络共同路径车辆密度的演化。我们证明该算法在交汇处自动选择可行解，因此通常在经典方法中使用的额外步骤（例如通过线性规划方法最大化流量）不再需要。由于用户无需显式处理交汇处的车辆动力学，数值代码可在几分钟内实现。我们对一种来自经典网络交通流理论的Godunov方法进行了详细数值比较，该方法在交汇处最大化流量。
英文摘要：
In this paper we propose a Godunov-based discretization of a hyperbolic system of conservation laws with discontinuous flux, modeling vehicular flow on a network. Each equation describes the density evolution of vehicles having a common path along the network. We show that the algorithm selects automatically an admissible solution at junctions, hence ad hoc external procedures (e.g., maximization of the flux via a linear programming method) usually employed in classical approaches are no needed. Since users have not to deal explicitly with vehicle dynamics at junction, the numerical code can be implemented in minutes. We perform a detailed numerical comparison with a Godunov-based scheme coming from the classical theory of traffic flow on networks which maximizes the flux at junctions.
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