本文提出一种协调能源与交通调度的框架，用于在时间约束下为智能城市提供电网支撑服务。具体考虑一种场景：分布式系统运营商在给定截止时间内要求特定电量。配备虚拟电池分区技术的网联自动驾驶电动汽车车队被动态调度至车网互联（V2G）站点。路径规划问题被建模为周期性更新的资源约束最短路径问题，综合考虑时间与能量约束，并采用基于动态交通模型推导的、依赖拥堵程度的行驶时间。在单车层面，采用模型预测控制策略调节车速，在满足出行能量需求的同时确保按时抵达。该框架在意大利拉帕洛（Rapallo）城市路网上的仿真验证表明，其对拥堵引发的延迟具有鲁棒性。

This paper proposes a coordinated energy-mobility dispatch framework for grid support service provision in smart cities under time constraints. In particular, a scenario in which a distributed system operator requests a specified amount of energy within a given deadline is considered. A fleet of connected autonomous electric vehicles equipped with virtual battery partitioning is dynamically dispatched toward vehicle-to-grid stations. The routing problem is formulated as a periodically updated resource-constrained shortest path, accounting for time and energy constraints with congestion-dependent travel times derived from a dynamic traffic model. At the vehicle level, a model predictive control strategy regulates speed to satisfy mobility energy requirements while ensuring deadline compliance. The framework is validated through simulations on the urban network of Rapallo (Italy), demonstrating robustness against congestion-induced delays.