基础设施网络是人类出行与交通的基础。提升单一链路的质量可局部改善网络性能。然而，高效的交通需要跨多链路路径的高质量连通走廊，这无法通过独立的单链路升级实现。本文提出一个评估多链路联合升级影响的框架，将其视为固有高阶交互，从而量化复杂交通网络中的链路协同效应。若一条链路的升级能增加另一条链路升级的收益，则二者具有协同性，这促进了同一路径上拓扑互补链路的升级，同时抑制了冗余平行链路的升级。通过将这种协同效应表示为整体网络性能的二阶导数，我们开发了一种高效计算框架，以识别形成连通网络骨干的协同链路。我们将该理论框架应用于德国汉堡市的实证街道网络与骑行需求数据，并结合城市自行车交通的扰动效用路径选择模型。研究结果揭示了源自高阶交互的协同效应，从而支持超越局部链路重要性的战略基础设施规划，适用于复杂的交通与流网络。

Infrastructure networks essentially underlie human mobility and transport. Improving the quality of single links increases network performance locally. However, efficient transport requires high-quality connected corridors across multi-link paths that do not emerge from independent single-link upgrades. Here, we introduce a framework for evaluating the impact of jointly upgrading multiple links as inherently higher-order interactions, enabling us to quantify link synergies in complex transport networks. Two links are synergistic if an upgrade of one increases the benefit of upgrading the other, promoting upgrades of topologically complementary links along the same path while discouraging upgrades of redundant parallel links. By expressing these synergies as second-order derivatives of overall network performance, we develop an efficient computational framework to identify synergistic links that form a connected network backbone. We apply our theoretical framework by combining empirical street network and cycling demand data for Hamburg, Germany, with a perturbed utility route choice model for urban bicycle traffic. Our results reveal synergies from higher-order interactions, thereby enabling strategic infrastructure planning that goes beyond local link importance in complex transport and flow networks.