Steinacker Christoph, Paulsen Mads, Schröder Malte, Rich Jeppe
Chair of Network Dynamics, Center for Advancing Electronics Dresden (cfaed) and Institute of Theoretical Physics, TUD Dresden University of Technology, 01062, Dresden, Germany.
Transportation Science Division, Department of Technology, Management and Economics, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
Sci Rep. 2025 May 3;15(1):15471. doi: 10.1038/s41598-025-99976-9.
Promoting active mobility like cycling relies on the availability of well-connected, high-quality bicycle networks. However, expanding these networks over an extended planning horizon presents one of the most complex challenges in transport science. This complexity arises from the intricate interactions between infrastructure availability and usage, such as network spillover effects and mode choice substitutions. In this paper, we approach the problem from two perspectives: direct optimization methods, which generate near-optimal solutions using operations research techniques, and conceptual heuristics, which offer intuitive and scalable algorithms grounded in network science. Specifically, we compare direct welfare optimization with an inverse network percolation approach to planning cycle superhighway extensions in Copenhagen. Interestingly, while the more complex optimization models yield better overall welfare results, the improvements over simpler methods are small. More importantly, we demonstrate that the increased complexity of planning approaches generally makes them more vulnerable to input uncertainty, reflecting the bias-variance tradeoff. This issue is particularly relevant in the context of long-term planning, where conditions change during the implementation of the planned infrastructure expansions. Therefore, while planning bicycle infrastructure is important and renders exceptionally high benefit-cost ratios, considerations of robustness and ease of implementation may justify the use of more straightforward network-based methods.
推广像骑自行车这样的主动出行方式依赖于连接良好、高质量的自行车网络的可用性。然而，在较长的规划期内扩展这些网络是交通科学中最复杂的挑战之一。这种复杂性源于基础设施可用性和使用之间的复杂相互作用，例如网络溢出效应和出行方式选择替代。在本文中，我们从两个角度来处理这个问题：直接优化方法，即使用运筹学技术生成近似最优解；概念启发式方法，即提供基于网络科学的直观且可扩展的算法。具体而言，我们将直接福利优化与一种反向网络渗流方法进行比较，以规划哥本哈根的自行车高速公路延伸段。有趣的是，虽然更复杂的优化模型能产生更好的总体福利结果，但相较于更简单的方法，其改进幅度较小。更重要的是，我们证明规划方法复杂性的增加通常会使其更容易受到输入不确定性的影响，这体现了偏差 - 方差权衡。在长期规划的背景下，这个问题尤为相关，因为在计划的基础设施扩展实施过程中情况会发生变化。因此，虽然规划自行车基础设施很重要且能带来极高的效益成本比，但对稳健性和实施便利性的考虑可能证明使用更直接的基于网络的方法是合理的。
