本文针对城市路网中因学校相关出行高度集中所引发的早高峰通勤拥堵问题，提出一种基于宏观基本图（MFD）的多区域城市网络校车始发时间调控双层优化框架，显式耦合系统级调控与基于多类用户均衡的出发时间选择行为。上层问题联合最小化总出行时间与当前校车时刻表的偏离程度；下层问题则通过确定性动态多类用户均衡模型刻画通勤者行为，该模型纳入了对出行时间、早到与迟到成本的 alpha-beta-gamma 偏好。为应对双层结构、非凸交通动力学及内生需求响应所带来的计算挑战，本文设计了一种在上下层问题间交替迭代的算法：上层问题被近似为可由标准数学规划求解器求解的形式，下层均衡问题则通过迭代算法获得近似解。数值实验结果表明该方法可显著缓解拥堵，并刻画了校车始发时间灵活性与交通效率之间的权衡关系。敏感性分析进一步考察了MFD不确定性及调度偏好参数的影响。

This paper addresses morning commute congestion caused by concentrated school-related trips in urban networks. We propose a bi-level optimization framework for regulating school start times in a multi-region urban network characterized by Macroscopic Fundamental Diagrams (MFDs), explicitly coupling system-level regulation with multi-class user-equilibrium-based departure-time choices. The Upper-Level problem jointly minimizes total time spent and deviations from current school schedules, while the Lower-Level problem models commuter behavior through a deterministic dynamic multi-class user equilibrium formulation incorporating alpha-beta-gamma preferences for travel time, earliness, and lateness costs. To address the computational challenges arising from the bilevel structure, non-convex traffic dynamics, and endogenous demand responses, an iterative algorithm alternating between the Upper- and Lower-Level problems is developed. The Upper-Level problem is approximated through a formulation solvable with standard mathematical programming solvers, while an iterative algorithm provides an approximate solution to the Lower-Level equilibrium problem. Numerical results demonstrate substantial congestion reductions and characterize the trade-off between school start-time flexibility and traffic efficiency. Sensitivity analyses further examine the effects of MFD uncertainty and scheduling preferences.