Safety resilience assessment of urban road traffic system under rainstorm waterlogging

doi:10.16265/j.cnki.issn1003-3033.2022.07.1391

Abstract

Abstract:

In order to evaluate the impact of a rainstorm waterlogging on the resilience of urban road traffic systems, the resilience network hierarchical model of the urban road traffic system was constructed by analyzing the safety resilience factors of the road traffic system. Four layers of networks were divided, including drainage network, road network, traffic network and emergency network, and the connotation and mechanism of the model were given. Combined with the hierarchical model, a resilience evaluation index system was designed. Furthermore, a qualitative and quantitative evaluation method of urban road traffic system resilience was given by using FAHP. Finally, a case study of a rainstorm waterlogging disaster in a region of Beijing was carried out. The results show that the resilience function curves of the system all decreased seriously after three rainfalls, with the decline ranges of 68.18%, 51.28% and 59.52%, respectively. The average resilience of the system is 0.57, and the resilience evaluation result is 0.53. The evaluation result is consistent with the example analysis. The proposed method can analyze the safety resilience, and evolution trend of urban road traffic systems under rainstorm waterlogging, realize the accurate evaluation of system safety resilience, and improve the management level of system safety resilience.

Keywords: ; ; ;;

Key words: rainstorm waterlogging, urban road traffic system, resilience assessment, resilience model, fuzzy analytic hierarchy process (FAHP)

TANG Shaohu, ZHU Wei, CHENG Guang, ZHENG Jianchun, ZHOU Jin. Safety resilience assessment of urban road traffic system under rainstorm waterlogging[J]. China Safety Science Journal, 2022, 32(7): 143-150.

Figures/Tables 16

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Tab.7

Statistical table of each network data change in three historical days in this region under rainstorm

日期	排水网络/(10⁶L·24h^-1)			道路网络/unit			交通网络/(veh·h^-1)			应急网络/unit
日期	$C 1 s$	$C 1 i$	$C - 1$	$C 2 s$	$C 2 i$	$C - 2$	$C 3 s$	$C 3 i$	$C - 3$	$C 4 s$	$C 4 i$	$C - 4$
2016-07-20	353.9	209.9	297.4	30.0	49.0	69.0	1 426.0	4 332.0	6 100.0	16.0	28.0	55.0
2017-06-22	250.9	231.7	297.4	36.0	56.0	69.0	1 658.0	4 951.0	6 100.0	24.0	39.0	55.0
2018-07-16	280.2	237.9	297.4	42.0	59.0	69.0	1 822.0	5 216.0	6 100.0	22.0	47.0	55.0

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Tab.8

Comparison of regional system resilience under three rainfall events

日期	韧性机能		系统韧性	平均韧性
日期	q₀	q₁	R	$R -$
2016-07-20	0.66	0.21	0.52	0.57
2017-06-22	0.78	0.38	0.61
2018-07-16	0.84	0.34	0.57

Tab.8

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评估目标	一级指标	二级指标
道路交通系统韧性U	排水网络U₁	管道设备设施性能、管网标准、关键节点措施针对性、应急资源保障能力
	道路网络U₂	道路设施性能、道路清障能力、道路防灾标准、应急资源保障能力
	交通网络U₃	交通应急管控能力、交通网络连通性、应急资源保障能力
	应急网络U₄	应急体制机制完备性、培训演练协同能力、应急资源保障能力

U	U₁	U₂	U₃	U₄
U₁	1	5	4	1
U₂	1/5	1	1/2	1/3
U₃	1/4	2	1	1/2
U₄	1	3	2	1

一级指标	二级指标	隶属度
一级指标	二级指标	强	较强	一般	较弱	弱
交通网络U₃	交通网络连通性	0.0	0.2	0.4	0.3	0.1
	交通应急管控能力	0.0	0.1	0.3	0.4	0.2
	应急资源保障能力	0.2	0.3	0.3	0.1	0.1

一级指标	二级指标	隶属度
一级指标	二级指标	强	较强	一般	较弱	弱
应急网络U₄	应急体制机制完备性	0.0	0.1	0.3	0.4	0.2
	培训演练协同能力	0.1	0.2	0.4	0.2	0.1
	应急资源保障能力	0.2	0.4	0.3	0.1	0.0