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Resilience analysis of urban road networks based on LSTM model for rainfall-induced day-to-day traffic flow degradation
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Hongwei WANG, Xiaobo RUAN**, Yulong LI, Yutao TANG, Jianxun DING
China Safety Science Journal | 2025, 35(12) : 213 - 220
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China Safety Science Journal | 2025, 35(12): 213-220
Public safety
Resilience analysis of urban road networks based on LSTM model for rainfall-induced day-to-day traffic flow degradation
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Hongwei WANG, Xiaobo RUAN**, Yulong LI, Yutao TANG, Jianxun DING
Affiliations
  • School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei Anhui 230009, China
Published: 2025-12-28 doi: 10.16265/j.cnki.issn1003-3033.2025.12.1472
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To explore the time-varying performance of urban road networks under regular rainfall and establish a reasonable evaluation system for road network resilience, an LSTM model for the rainfall-induced traffic flow degradation in urban road segments was first constructed, and a network performance function with time-varying characteristics was second defined. Then, based on the resilience concept, a time-varying resilience calculation model for road networks was derived. Finally, the effect of rainfall on the time-varying characteristics of road segments and networks was investigated based on rainfall information and traffic data of a certain city and the Sioux Falls network. The results show that when the duration or amount of rainfall increases, the traffic flow degradation of road segments increases on weekdays. The road network resilience is a comprehensive reflection of the synergistic effect of various related road segments, and therefore its response to rainfall is slower than that of traffic flow degradation, and its value is generally not less than 0.9 under regular rainfall conditions. The road network resilience during low rainfall seasons is significantly stronger than that during high rainfall seasons, and the annual resilience of road networks is usually maintained at a higher level when not affected by rainfall disasters, and the difference between adjacent years is not significant.

day-to-day traffic flow  /  rainfall-induced degradation  /  long short-term memory (LSTM)  /  urban road networks  /  road network resilience
Hongwei WANG, Xiaobo RUAN, Yulong LI, Yutao TANG, Jianxun DING. Resilience analysis of urban road networks based on LSTM model for rainfall-induced day-to-day traffic flow degradation[J]. China Safety Science Journal, 2025 , 35 (12) : 213 -220 . DOI: 10.16265/j.cnki.issn1003-3033.2025.12.1472
Year 2025 volume 35 Issue 12
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doi: 10.16265/j.cnki.issn1003-3033.2025.12.1472
  • Receive Date:2025-07-10
  • Online Date:2026-07-09
  • Published:2025-12-28
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  • Received:2025-07-10
  • Revised:2025-10-11
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    School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei Anhui 230009, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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