Influence of Waterlogging on Topological Potential of Urban Traffic Network Neighborhood

JIN Liang-hai; PENG Shuang; YANG Ying-liu; CHEN Shu; SHAO Bo; CHEN Yun

doi:10.11988/ckyyb.20211086

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Journal of Changjiang River Scientific Research Institute ›› 2023, Vol. 40 ›› Issue (3) : 68-73. DOI: 10.11988/ckyyb.20211086

WATER-RELATED DISASTERS

Influence of Waterlogging on Topological Potential of Urban Traffic Network Neighborhood

JIN Liang-hai^1,2,3, PENG Shuang⁴, YANG Ying-liu¹, CHEN Shu^1,3, SHAO Bo^1,3, CHEN Yun^1,3

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Abstract

In an attempt to quantify the impact of waterlogging on urban road network traffic operation, the neighborhood topological potential of the waterlogged urban traffic road network was researched. First, the dual topological diagram of the urban road network was constructed with road sections mapped as points and intersections as edges. Subsequently, according to the principle of the potential function, parameters including the shortest topological distance between nodes, the relief height difference transfer weight, the throughput at dual nodes of road network, and the influence of potential field were determined. On this basis, a neighborhood topological model of the impact of waterlogging on urban traffi network was established, and the model was solved by using the golden section optimization algorithm. The model was applied to analyze the evolution of topological potential of urban road network under different depths of waterlogging in the flood-prone area in Xiling District of Yichang City as a case study. Results demonstrate that when the depth of waterlogging reaches 15 cm or more, the topological potential of each road section decreases by over 20%. With the increase of waterlogging depth at peak and flat times, the topological potential of nodes fluctuates gently before sharp decline. The topological potential value reaches the maximum between Xiling 1^st Road in waterlogging section and the road section in the first-level domain; but reduces between other road sections as distance increases. The study reveals the law of the influence of waterlogging on the neighborhood topology of urban traffic road networks, and is expected to provide a theoretical basis for urban waterlogging management and traffic control.

Key words

waterlogging / urban road network / topological potential / evolution characteristics / golden section algorithm

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JIN Liang-hai, PENG Shuang, YANG Ying-liu, CHEN Shu, SHAO Bo, CHEN Yun. Influence of Waterlogging on Topological Potential of Urban Traffic Network Neighborhood[J]. Journal of Changjiang River Scientific Research Institute. 2023, 40(3): 68-73 https://doi.org/10.11988/ckyyb.20211086

References

[1] 戴维·R·戈德沙尔克, 许婵. 城市减灾: 创建韧性城市[J]. 国际城市规划, 2015, 30(2): 22-29.
[2] 易嘉伟, 王楠, 千家乐, 等. 基于大数据的极端暴雨事件下城市道路交通及人群活动时空响应[J]. 地理学报, 2020, 75(3): 497-508.
[3] 张健沛, 李泓波, 杨静, 等. 基于拓扑势的网络社区结点重要度排序算法[J]. 哈尔滨工程大学学报, 2012, 33(6): 745-752.
[4] XU F, HE Z, SHA Z, et al. Assessing the Impact of Rainfall on Traffic Operation of Urban Road Network[J]. Procedia-Social and Behavioral Sciences, 2013, 96: 82-89.
[5] MITSAKIS E, STAMOS I, DIAKAKIS M, et al. Impacts of High-Intensity Storms on Urban Transportation: Applying Traffic Flow Control Methodologies for Quantifying the Effects[J]. International Journal of Environmental Science and Technology, 2014, 11(8): 2145-2154.
[6] STAMOS I, MITSAKIS E, SALANOVA J M, et al. Impact Assessment of Extreme Weather Events on Transport Networks: a Data-Driven Approach[J]. Transportation Research Part D: Transport and Environment, 2015, 34: 168-178.
[7] 胡文燕, 李梦雅, 王军, 等. 暴雨内涝影响下的城市道路交通拥挤特征识别[J]. 地理科学进展, 2018, 37(6): 772-780.
[8] 易嘉伟, 王楠, 千家乐, 等. 基于大数据的极端暴雨事件下城市道路交通及人群活动时空响应[J]. 地理学报, 2020, 75(3): 497-508.
[9] YANG C L, SUTRISNO H, CHAN A S, et al. Identification and Analysis of Weather-Sensitive Roads Based on Smartphone Sensor Data: a Case Study in Jakarta[J]. Sensors (Basel, Switzerland), 2021, 21(7): 2405.
[10] 李岩, 南斯睿, 马静, 等. 降雨天气单点交叉口交通信号控制优化方法[J]. 交通运输工程学报, 2018, 18(5): 185-194.
[11] MA F, LIU F, YUEN K F, et al. Cascading Failures and Vulnerability Evolution in Bus-Metro Complex Bilayer Networks under Rainstorm Weather Conditions[J]. International Journal of Environmental Research and Public Health, 2019, 16(3): 329.
[12] NI X, HUANG H, CHEN A, et al. Effect of Heavy Rainstorm and Rain-Induced Waterlogging on Traffic Flow on Urban Road Sections: Integrated Experiment and Simulation Study[J]. Journal of Transportation Engineering, Part A: Systems, 2021, 147(10): 4021057.
[13] 韦伟, 毛保华, 陈绍宽, 等. 基于时空自相关的道路交通状态聚类方法[J]. 交通运输系统工程与信息, 2016, 16(2): 57-63.
[14] HAN Z M,CHEN Y,LI M Q,et al. An Efficient Node Influence Metric Based on Triangle in Complex Networks[J]. Acta Physica Sinica, 2016, 65(16): 168901.
[15] 刘刚,李永树,杨骏,等. 对偶图节点重要度的道路网自动选取方法[J]. 测绘学报,2014,43(1):97-104.
[16] MUNKRES J R. Elements of Algebraic Topology[M]. Boca Raton:CRC Press,1993.
[17] WANG T, HAN Y, WU J. Evaluate Nodes Importance in Directed Network Using Topological Potential[C]//2010 2nd International Conference on Information Engineering and Computer Science. December 25-26, 2010, Wuhan, China. New York: IEEE Press, 2010: 1-4.
[18] 淦文燕, 赫南, 李德毅, 等. 一种基于拓扑势的网络社区发现方法[J]. 软件学报, 2009, 20(8): 2241-2254.
[19] 李泓波, 张健沛, 杨静, 等. 基于拓扑势的重叠社区及社区间结构洞识别: 兼论结构洞理论视角下网络的脆弱性[J]. 电子学报, 2014, 42(1): 62-69.
[20] 中华人民共和国住房和城乡建设部.住房城乡建设部关于公布2018年全国城市排水防涝安全及重要易涝点整治责任人名单的通告[EB/OL].(2018-03-19)[2021-05-31].http://www.mohurd.gov.cn/wjfb/201803/t20180319_235423.html.
[21] 杜磊, 杨晓宽. 不同道路积水情况对交通影响及造成损失的研究[C]//科技创新绿色交通——第十一次全国城市道路交通学术会议论文集. 大连, 2011: 389-393.
[22] YIN J, YU D, LIN N, et al. Evaluating the Cascading Impacts of Sea Level Rise and Coastal Flooding on Emergency Response Spatial Accessibility in Lower Manhattan, New York City[J]. Journal of Hydrology, 2017, 555: 648-658.