交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (4): 101-111.DOI: 10.16097/j.cnki.1009-6744.2026.04.009

• 综合交通运输体系 • 上一篇    下一篇

极端降雨下城市“交通-充电”耦合网络修复时序优化

罗昊1，王明涛1，杨洋*1，王文成2，黄海博1，袁振洲1，李哲1   

  1. 1.北京交通大学，交通运输学院，北京 100044；2.北京市城市规划设计研究院，北京 100045
  • 收稿日期:2026-04-23 修回日期:2026-05-13 接受日期:2026-05-22 出版日期:2026-08-25 发布日期:2026-08-21
  • 作者简介:罗昊（1986— ），男，河北怀来人，高级实验师
  • 基金资助:
    国家自然科学基金 (52572336)

Repair Sequencing Optimization of Urban Coupled Traffic-Power Networks Under Extreme Rainfall

LUO Hao1 , WANG Mingtao1, YANG Yang*1, WANG Wencheng2, HUANG Haibo1, YUAN Zhenzhou1, LI Zhe1   

  1. 1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China; 2. Beijing Municipal Institute of City Planning & Design, Beijing 100045, China
  • Received:2026-04-23 Revised:2026-05-13 Accepted:2026-05-22 Online:2026-08-25 Published:2026-08-21
  • Supported by:
    National Natural Science Foundation of China (52572336)

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摘要： 针对极端暴雨内涝下城市交通与新能源汽车（New Energy Vehicles, NEVs）充电网络耦合失效及应急协同恢复难题，本文提出一种面向服务释放的路网抢修时序优化策略。首先，刻画灾害场景下“路网断裂-拓扑孤岛”跨层映射机理，以最大化系统服务效能释放率（System Service Efficacy Release Rate, SSR）及其恢复曲线下面积（Area Under the Curve, AUC）为目标构建时序优化模型。其次，为克服高度碎裂网络中启发式搜索易陷入非连通冗余修复与长期无收益的困境，提出基于重力路由的自适应边界拓扑(Gravity-Routed Adaptive Frontier Topology, GRAFT)算法。该算法通过动态作业面约束严格规避脱网无效修复，并引入孤岛重力场兜底机制引导抢修资源在连续无增益阶段维持有效推进。基于北京市海淀区大规模交能耦合路网的仿真结果表明，所提算法的全周期恢复效能（AUC为57.58）稳定优于传统的需求优先（54.43）、拓扑优先（52.83）和可达性优先（52.77）策略，展现出更高的累积恢复效益；消融实验显示，动态作业面约束将脱网无效修复动作清零，配合重力场机制使高价值枢纽站的触达时间提前至第36小时；敏感性分析揭示了资源受限工况下抢修投入规模与系统恢复效能之间的非线性关系及边际递减效应。研究结果定量证实 了底层交通网络连通性对上层充电服务能力的支撑作用，可为城市防汛减灾与跨部门协同应急资源配置提供理论依据。

关键词: 交通工程, 修复时序优化, 自适应边界拓扑算法, 交能耦合系统, 交通网络韧性, 公共充电网络

Abstract: To address the challenges of coupled failures and collaborative emergency recovery in urban transportation and public New Energy Vehicles (NEVs) charging networks under extreme rainstorm-induced waterlogging, this study proposes a service-release-oriented optimization strategy for road network repair sequencing. First, the cross-layer mapping mechanism from "road network disruption" to "topological islands" is characterized within disaster scenarios. A temporal optimization model is developed to maximize the System Service Efficacy Release Rate (SSR) and the corresponding Area Under the Curve (AUC). Then, the Gravity-Routed Adaptive Frontier Topology algorithm is introduced to mitigate the limitations of heuristic searches, specifically their susceptibility to disconnected redundant repairs and sparse rewards in fragmented networks. This algorithm strictly circumvents off-network invalid repairs through a dynamic frontier constraint and incorporates an isolated island gravity field fallback mechanism. This mechanism effectively guides repair resources through zero-return windows, prioritizing the reconnection of high-capacity charging hubs. Simulation results from a large-scale coupled traffic-power network in Haidian District, Beijing, demonstrate that the algorithm achieves a full-cycle recovery performance (AUC is 57.58) that consistently outperforms traditional strategies based on demand- priority (54.43), topology- priority (52.83), and reachability- priority (52.77). Ablation experiments confirm that the dynamic frontier constraint eliminates off- network invalid repairs, while the gravity field mechanism advances the reconnection of high-value hub stations to the 36th hour. Sensitivity analysis reveals a non-linear relationship and diminishing marginal returns between repair investment scale and system recovery efficacy under resource constraints. These findings quantitatively demonstrate the critical role of underlying traffic network connectivity in supporting upper- layer charging services, providing a theoretical foundation for urban flood control and collaborative emergency resource allocation.

Key words: traffic engineering, repair sequencing optimization, adaptive frontier topology algorithm, coupled traffic-power system, transportation network resilience, public charging network

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