﻿ 火车站出站口行人疏散方案优化设计分析 Optimal Design of Pedestrian Evacuation Schemes at Exit of Railway Station

Open Journal of Transportation Technologies
Vol. 08  No. 01 ( 2019 ), Article ID: 28423 , 7 pages
10.12677/OJTT.2019.81005

Optimal Design of Pedestrian Evacuation Schemes at Exit of Railway Station

Xuecen Bai, Xingli Li*, Zhongfei Geng

School of Applied Science, Taiyuan University of Science and Technology, Taiyuan Shanxi

Received: Dec. 21st, 2018; accepted: Jan. 4th, 2019; published: Jan. 11th, 2019

ABSTRACT

In recent years, the probability of sudden events in crowded public places has greatly increased. This paper takes the exit of the railway station with huge passenger flow as the research object. The impact of different evacuation schemes on pedestrian evacuation efficiency at the exit of the railway station is simulated by using Anylogic simulation software. The spatio-temporal dynamics during the evacuation process is analyzed. The simulation results show that the overall evacuation efficiency can be greatly improved by classifying pedestrians in advance and allowing pedestrians to evacuate according to categories. In addition, reasonable allocation of different types of pedestrian access ratio will be helpful for pedestrian evacuation.

Keywords:Station Exit, Pedestrian Evacuation, Simulation, Scheme Optimization

1. 引言

2. 建立模型

2.1. 行人特性分析

2.2. 模型介绍

Anylogic中提供的行人库基于社会力模型，能够模拟仿真行人流。本文针对一个宽度为9米，长度为15米的火车站出站口进行建模仿真 [16]，模型如图1所示。其中紫色实线代表入口，红色实线代表出口，黑色实线、蓝色实线及矩形方块分别代表墙壁、栏杆及障碍物，行人不能翻越墙壁和障碍物。红色实心圆代表未携带行李的正常行人，蓝色实心圆代表携带行李的正常行人，绿色实心圆代表特殊行人。考虑到一列火车其核载人数约为1000，本文假设行人总数为1000，全部为单向行人流，由入口到达出站口。如无特殊说明，各类行人参数设置 [16] 如表1

Figure 1. Model diagram

Table 1. Pedestrian parameter settings

3. 仿真及优化

3.1. 仿真结果与分析

Figure 2. Simulation diagram of pedestrian evacuation under emergency at t = 180 s

3.2. 优化方案及对比

(a) t = 180 s (b) t = 600 s

Figure 3. The spatio-temporal patterns of scheme 1

(a) t = 180 s (b) t = 600 s

Figure 4. The spatio-temporal patterns of scheme 2

(a) t = 120 s (b) t = 360 s (c) t = 420 s

Figure 5. The spatio-temporal patterns of scheme 3

(a) t = 120 s (b) t = 360 s (c) t = 420 s

Figure 6. The spatio-temporal patterns of scheme 4

Table 2. Simulation time required for different schemes

4. 结论

Optimal Design of Pedestrian Evacuation Schemes at Exit of Railway Station[J]. 交通技术, 2019, 08(01): 38-44. https://doi.org/10.12677/OJTT.2019.81005

1. 1. Helbing, D. (2000) Traffic and Related Self-Driven Many-Particle Systems. Physics, 73, 1067-1141.

2. 2. Henderson, L.F. (1971) The Statistics of Crowd Fluids. Nature, 229, 381-383. https://doi.org/10.1038/229381a0

3. 3. Hoogendoorn, S.P., Wagenin-gen-Kessels, F.V., Daamen, W., et al. (2015) Continuum Theory for Pedestrian Traffic Flow: Local Mute Choice Modelling and Its Implications. Transportation Research Part C, 59, 183-197. https://doi.org/10.1016/j.trc.2015.05.003

4. 4. Helbing, D. and Molnar, P. (1995) Social Force Model for Pedestrian Dynamics. Physical Review E, 51, 4282. https://doi.org/10.1103/PhysRevE.51.4282

5. 5. Helbing, D., Farkas, I. and Vicsek, T. (2000) Simulating Dynamical Features of Escape Panic. Nature, 407, 487-490. https://doi.org/10.1038/35035023

6. 6. Chraibi, M., Seyfried, A. and Schadschneider, A. (2010) Generalized Centrifugal Force Model for Pedestrian Dynamics. Physical Review E, 82, Article ID: 046111. https://doi.org/10.1103/PhysRevE.82.046111

7. 7. Burstedde, C., Klauck, K. and Schadschneider, A. (2001) Simulation of Pedestrian Dynamics Using a Two-Dimensional Cellular Automaton. Physica A, 295, 507-525. https://doi.org/10.1016/S0378-4371(01)00141-8

8. 8. Kirchner, A. and Schadschneider, A. (2002) Simulation of Evacuation Processes Using a Bionics-Inspired Cellular Automaton Model for Pedestrian Dynamics. Physica A, 312, 260-276. https://doi.org/10.1016/S0378-4371(02)00857-9

9. 9. Zhang, P., Jian, X.X., Wong, S.C., et al. (2012) Potential Field Cellular Automata Model for Pedestrian Flow. Physical Review E, 85, Article ID: 021119. https://doi.org/10.1103/PhysRevE.85.021119

10. 10. Jian, X.X., Wong, S.C., Zhang, P., et al. (2014) Perceived Cost Potential Field Cellular Automata Model with an Aggregated Force Field for Pedestrian Dynamics. Transportation Research Part C, 42, 200-210. https://doi.org/10.1016/j.trc.2014.01.018

11. 11. Tajima, Y. and Nagatani, T. (2001) Scaling Behavior of Crowd Flow Outside a Hall. Physica A, 292, 545-554. https://doi.org/10.1016/S0378-4371(00)00630-0

12. 12. Helbing, D., Isobe, M., Nagatani, T., et al. (2003) Lattice Gas Simulation of Experimentally Studied Evacuation Dynamics. Physical Review E, 67, Article ID: 067101. https://doi.org/10.1103/PhysRevE.67.067101

13. 13. Kuang, H., Li, X., Song, T., et al. (2008) Analysis of Pedestrian Dynamics in Counter Flow via an Extended Lattice Gas Model. Physical Review E, 78, Article ID: 066117. https://doi.org/10.1103/PhysRevE.78.066117

14. 14. 岳昊. 基于元胞自动机的行人疏散流仿真研究[J]. 物理学报, 2009, 58(7): 4523-4530.

15. 15. 谢积鉴, 薛郁. 通过博弈的室内行人疏散动力学研究[J]. 物理学报, 2012, 61(19): 275-281.

16. 16. 吴中, 施雯. 基于Anylogic的行人换乘通道入口优化设计[J]. 贵州大学学报: 自然科学版, 2013, 30(6): 130-133.

17. 17. 罗培卿, 李续扬. 铁路车站人员应急疏散仿真研究[J]. 交通科技与经济, 2015, 17(4): 82-85.

18. 18. 李孟洁. 火车站旅客疏散行为统计分析及应用研究[J]. 防灾科技学院学报, 2013, 15(2): 57-62.

19. 19. 张晨杰, 程旭东, 张洪江. 火车站出站大厅火灾人员疏散预案的制定[J]. 消防科学与技术, 2008, 27(7): 509-511.

20. 20. 李伏京, 方卫宁, 胡清梅, 等. 地铁车辆安全疏散性能的仿真研究[J]. 系统仿真学报, 2006, 18(4): 852-855．

21. NOTES

*通讯作者。