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时变条件下基于路径冗余识别关键路段方法

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针对道路网络路径冗余性的关键道路识别研究不仅有助于提高日常出行的效率,更在灾害应急时为救援和疏散提供重要的路径备选方案.本文提出了关键道路识别模型,该模型全面考虑了道路系统中的时变因素,包括出行起讫点(origin-destination,OD)需求、OD对(OD pair)以及道路交通网络的拥挤状况;通过分析每个时段下的时变因素,计算当前时段的道路网络路径冗余性;结合每个时段的权重和对应的道路网络路径冗余性,得到道路网络路径冗余性的期望值,从而准确地识别关键路段;为解决求解大规模路径冗余性带来的计算挑战,通过对城市道路网络结构进行重构,利用具有多项式计算时间性质的最大流和最小费用流算法迭代求解,实现模型的快速求解.本文在平陆运河桥梁群拆除重建工程的实际应用中,验证了模型和算法的有效性和适用性;结果表明:通过分析桥梁群在拆除重建前后对钦州市道路网络冗余性的影响,揭示了 OD对路径冗余性的变化情况,从而为施工前后实施精细化的交通管理措施提供了依据;在计算效率方面,与商业软件Gurobi相比,计算时间提高了 17.90倍,证明了其在处理大规模现实城市道路网络中的适用性.本文可以可以针对性地增强关键路段的抗灾能力,从而有助于构建1个更具抗灾救灾能力的城市道路交通系统.
A Method for Identifying Key Links Based on Path Redundancy Under Time-Varying Conditions
The study focuses on a model for identifying critical road links based on path redundancy in road net-works.Path redundancy enhances efficiency for daily travel and provides crucial alternative routes during emergen-cy situations.This model comprehensively considers time-varying factors in the road system,including origin-desti-nation(OD)demand,OD pair,and road congestion.By analyzing time-varying factors for each period,the path re-dundancy of the road network is calculated.Furthermore,combining the weights of each period with their corre-sponding path redundancy yields the expected value of path redundancy,facilitating accurate identification of criti-cal links.To address the computational challenge of solving for large-scale path redundancy,a reconstruction of the urban road network structure is performed,enabling the use of maximum flow and minimum cost flow algorithms,which have polynomial time complexity,for iterative solutions.The effectiveness and applicability of the model and algorithm are verified through practical application in the Pinglu Canal bridge reconstruction project.Results reveal the impact of the bridge group's removal and reconstruction on the redundancy of the road network in Qinzhou.Changes in OD pair path redundancy are highlighted,providing a basis for refined traffic management measures be-fore and after construction.In terms of computational efficiency,the proposed algorithm shows a significant advan-tage over Gurobi.The computation time improves by 17.90 times,demonstrating its suitability for large-scale urban road networks.This paper can be targeted to enhance the resilience of key road sections,thereby contributing to the construction of a more resilient urban road transport system.

transportation engineeringcritical linkstime-varyingpath redundancydistinct pathPingLu Canal

龚华天、杨晓光

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同济大学城市交通研究院 上海 201804

同济大学交通学院 上海 201804

交通工程 关键路段 时变 路径冗余 独立路径 平陆运河

2024

交通信息与安全
武汉理工大学 交通计算机应用信息网

交通信息与安全

CSTPCD北大核心
影响因子:0.598
ISSN:1674-4861
年,卷(期):2024.42(5)