非平衡统计物理中的一个基本问题是：在强驱动系统中，有效平衡行为是否能在粗粒化尺度上出现。本文通过分析涵盖数百万旅行者的五年城际流动数据，研究了这一问题在人类移动背景下的表现。尽管短期流动高度不对称，但经过时间粗粒化后，超过一半的城市对趋于实现有效的流动平衡，归一化的方向不平衡随幂律衰减。其余城市对则表现出持续的漂移主导流或两种极端之间的交叉过渡。一种将移动分解为方向性漂移与关联涨落的随机模型定量捕捉了所有三种模式的共存。直接测量的涨落过程方差标度证实其接近扩散行为，且存在依赖于状态的偏差。这些结果表明，大规模移动网络呈现出从破坏到恢复流动对称性的尺度依赖性转变，对运输与传播动力学建模具有直接意义。

A fundamental question in nonequilibrium statistical physics is whether effective equilibrium behavior can emerge at coarse-grained scales in strongly driven systems. Here, we investigate this question in the context of human mobility by analyzing five years of intercity flow data covering millions of travelers. While short-term flows are highly asymmetric, temporal coarse-graining reveals that over half of all city pairs converge toward effective flow balance, with normalized directional imbalance decaying as a power law. The remaining pairs either exhibit persistent drift-dominated currents or a crossover between these two extremes. A stochastic model decomposing mobility into directional drift and correlated fluctuations quantitatively captures the coexistence of all three regimes. Directly measured variance scaling of the fluctuation process confirms near-diffusive behavior with regime-dependent deviations. These results demonstrate that large-scale mobility networks exhibit a scale-dependent transition from broken to restored flow symmetry, with direct implications for modeling transport and spreading dynamics.