面向地铁运营中断的多模式疏散策略

doi:10.13229/j.cnki.jdxbgxb.20250150

摘要/Abstract

摘要：

针对地铁运营中断场景下，现有研究多仅依靠应急接驳公交开展客流疏散，较少考虑多模式出行协同疏散的问题，提出了一种结合应急公交与应急出租车的多模式应急疏散策略。首先，构建多模式应急接驳模型，旨在最小化乘客出行延误及应急疏散成本；然后，设计遗传算法进行求解；最后，以福州市地铁1号线早高峰区间双向运营中断为案例，验证本文模型及算法的有效性。结果表明，相较于单一的应急公交策略，多模式疏散策略使综合成本和乘客出行时间成本分别降低了9.2%和22.4%。

关键词: 城市交通, 地铁运营中断, 乘客出行方式选择, 多模式疏散策略, 遗传算法

Abstract:

A multi-modal emergency evacuation strategy combining emergency buses and emergency cabs is proposed for the problem that existing studies mostly relied only on emergency shuttle buses for passenger flow evacuation under metro operation disruption scenarios， with little consideration given to coordinated evacuation via multi?mode travel. First， a multi-modal emergency access model is constructed to minimize passenger travel delays and reduce emergency evacuation costs. Then， a genetic algorithm is designed to solve the problem. Finally， the two-way operational disruptions in the morning peak interval of metro line 1 in Fuzhou City are used as a case study to verify the effectiveness and practicality of the model and algorithm. The results show that compared with the single bridging bus strategy， the multi-modal evacuation strategy achieves a reduction of 9.2% and 22.4% in the total cost and passenger travel time cost， respectively.

Key words: urban traffic, metro operation disruption, passenger travel mode choices, multi-modal evacuation strategy, genetic algorithm

中图分类号:

U491

赖元文,巫扬帆,梁健鸿,蔡元臣,王书易. 面向地铁运营中断的多模式疏散策略[J]. 吉林大学学报(工学版), 2026, 56(9): 2340-2349.

Yuan-wen LAI,Yang-fan WU,Jian-hong LIANG,Yuan-chen CAI,Shu-yi WANG. Multi⁃modal evacuation strategies for metro operational disruptions[J]. Journal of Jilin University(Engineering and Technology Edition), 2026, 56(9): 2340-2349.

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地铁站点	公交驻车点	驻车点编号	可用车辆数/辆	指派时间/min
南门兜（S₉）	道山路口公交站	Z₁	3	4
	仁德枢纽场站	Z₂	8	4
	福州高速指挥中心	Z₃	8	14
三叉街（S₁₃）	公交专用停车场	Z₄	5	10
	公交集团亚峰停车场	Z₅	6	10
	公交驾校停车场	Z₆	8	8

站点编号	最短行驶距离/km	站点编号	最短行驶距离/km
S₁~S₂	1.7	S₁₃~S₁₄	1.4
S₂~S₃	1.1	S₁₄~S₁₅	1.2
S₃~S₄	2.4	S₁₅~S₁₆	0.9
S₄~S₅	1.6	S₁₆~S₁₇	1.2
S₅~S₆	0.9	S₁₇~S₁₈	0.8
S₆~S₇	1.2	S₁₈~S₁₉	1.1
S₇~S₈	1.3	S₁₉~S₂₀	1.7
S₈~S₉	0.8	S₂₀~S₂₁	1.5
S₉~S₁₀	0.9	S₂₁~S₂₂	1.0
S₁₀~S₁₁	1.6	S₂₂~S₂₃	1.4
S₁₁~S₁₂	2.5	S₂₃~S₂₄	3.0
S₁₂~S₁₃	1.1	S₂₄~S₂₅	0.7

D	O
D	S₉	S₁₀	S₁₁	S₁₂	S₁₃
S₉	0	436	404	284	233
S₁₀	178	0	8	14	104
S₁₁	223	12	0	9	232
S₁₂	505	33	2	0	87
S₁₃	671	353	237	196	0

D	O
D	S₉	S₁₀	S₁₁	S₁₂	S₁₃
S₉	0	0.243 9	0.217 6	0.226 6	0.240 4
S₁₀	0.243 9	0	0.206 5	0.208 6	0.207 9
S₁₁	0.217 6	0.206 5	0	0.222 7	0.218 3
S₁₂	0.226 6	0.208 6	0.222 7	0	0.232 6
S₁₃	0.240 4	0.207 9	0.218 3	0.232 6	0

D	O
D	S₉	S₁₀	S₁₁	S₁₂	S₁₃
S₉	0	0.294 1	0.327 5	0.329 6	0.324 2
S₁₀	0.294 1	0	0.323 7	0.327 7	0.335
S₁₁	0.327 5	0.323 7	0	0.314 9	0.321 6
S₁₂	0.329 6	0.327 7	0.314 9	0	0.280 4
S₁₃	0.324 2	0.335	0.321 6	0.280 4	0