考虑行人微观差异的社会力避让模型与仿真

李一波, 刘自博

交通运输研究 ›› 2023, Vol. 9 ›› Issue (2) : 33-41.

交通运输研究 ›› 2023, Vol. 9 ›› Issue (2) : 33-41. DOI: 10.16503/j.cnki.2095-9931.2023.02.004
理论与方法

考虑行人微观差异的社会力避让模型与仿真

作者信息 +

A Social Force Avoidance Model and Simulation Considering Micro Differences of Pedestrians

  • LI Yi-bo ,  
  • LIU Zi-bo
Author information +
文章历史 +

摘要

为解决城市客运交通枢纽场景中行人仿真存在的冲突次数过多和不合理的震荡现象,基于社会力模型,引入主动避让力,针对行人的避让行为进行研究。因不同行人的微观特征不同,其期望速度存在较大差异,在避让力模型中引入期望速度差,将期望速度作为判断行人避让程度的关键指标,突出避让时行人的差异化选择。通过Matlab进行仿真实验,将仿真结果与真实通道内行人的移动路径进行对比。研究结果表明,期望速度更大的强势个体会更主动地进行避让,改进后的模型可以更好地还原差异化的避让行为,对行人路径的模拟误差较未引入避让力的模型降低了43.4%,改进的社会力模型仿真中不合理的碰撞现象减少了49.3%,且可以再现同向行人之间的超越行为。这表明改进后的模型能更好地还原行人对冲突的避让行为,可用于人群较为复杂场所的行人仿真。

Abstract

In order to solve the problems of too many conflicts and unreasonable oscillation in pedestrian simulation in urban passenger transport hubs, the active avoidance force was introduced to study the avoidance behavior of pedestrians based on the social force model. Considering that there are great differences in pedestrians′ expected speeds due to their different microscopic characteristics, the expected speed difference was introduced into the avoidance force model and was taken as the key index for judging the degree of pedestrian avoidance, to highlight the differentiated choices of pedestrians in avoidance. Finally, a simulation experiment was conducted using Matlab to compare the simulation results of the model constructed with the movement paths of pedestrians in real channels. The results showed that the stronger individuals with higher expected speed would be more active in avoiding, and the improved model could better restore the differentiated avoidance behavior; the simulation error of pedestrian path was reduced by 43.4% compared with the model without avoidance force; the unreasonable collision phenomenon in the simulation of improved social force model was reduced by 49.3%. It means that the improved model can better demonstrate pedestrians' avoidance behaviors toward conflicts, and can be used for pedestrian simulation in places with complex crowds.

关键词

行人仿真 / 社会力模型 / 避让力 / 期望速度 / 微观特征

Key words

pedestrian simulation / social force model / avoidance force / expected speed / microscopic feature

引用本文

导出引用
李一波, 刘自博. 考虑行人微观差异的社会力避让模型与仿真[J]. 交通运输研究. 2023, 9(2): 33-41 https://doi.org/10.16503/j.cnki.2095-9931.2023.02.004
LI Yi-bo, LIU Zi-bo. A Social Force Avoidance Model and Simulation Considering Micro Differences of Pedestrians[J]. Transport Research. 2023, 9(2): 33-41 https://doi.org/10.16503/j.cnki.2095-9931.2023.02.004
中图分类号: U491.2   

参考文献

[1]
HELBING D, BUZNA L, JOHANSSON A, et al. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions[J]. Transportation Science, 2005, 39(1): 1-24.
[2]
BURSTEDDE C, KLAUCK K, SCHADSCHNEIDER A, et al. Simulation of pedestrian dynamics using a two-dimensional cellular automaton[J]. Physica A: Statal Mechanics and Its Applications, 2001, 295(3-4): 507-525.
[3]
SHI J, REN A, CHI C. Agent-based evacuation model of large public buildings under fire conditions[J]. Automation in Construction, 2009, 18(3): 338-347.
[4]
HELBING D, MOLNAR P. Social force model for pedestrian dynamics[J]. Physical Review A: Atomic, Molecular, and Optical Physics, 1995, 51(5): 4282-4286.
[5]
HELBING D, FARKAS I, VICSEK T. Simulating dynamical features of escape panic[J]. Nature, 2000, 407(6803): 487-490.
[6]
WANG Q L, DONG H R, NING B, et al. Two-time-scale hybrid traffic models for pedestrian crowds[J]. IEEE Transactions on Intelligent Transportation Systems, 2018: 1-12.
[7]
PARISI D R, GILMAN M, MOLDOVAN H. A modification of the social force model can reproduce experimental data of pedestrian flows in normal conditions[J]. Physica A: Statistical Mechanics and its Applications, 2009, 388(17): 3600-3608.
[8]
MOUSSAID M, HELBING D, THERAULAZ G. How simple rules determine pedestrian behavior and crowd disasters[J]. Proceedings of the National Academy of Sciences, 2011, 108(17): 6884-6888.
[9]
ZANLUNGO F, IKEDA T, KANDA T. Social force model with explicit collision prediction[J]. EPL (Europhysics Letters), 2011, 93(6): 68005.
[10]
WANG Q L, CHEN Y, DONG H R, et al. A new collision avoidance model for pedestrian dynamics[J]. Chinese Physics B, 2015, 24(3): 457-466.
[11]
LI Q R, LIU Y, KANG Z X, et al. Improved social force model considering conflict avoidance[J]. Chaos, 2020, 30(1): 013129.
[12]
KOSTER G, TREML F, GODEL M. Avoiding numerical pitfalls in social force models[J]. Physical Review E: Statistical Nonlinear & Soft Matter Physics, 2013, 87(6): 063305.
[13]
FARIN F, FONTANELLI D, GARULLI A, et al. When Helbing meets Laumond: The headed social force model[J]. Decision & Control, IEEE, 2016: 3548-3553.
[14]
马尚, 张蕊, 齐泽阳, 等. 对向行人避让与接触行为社会力模型改进研究[J]. 计算机仿真, 2021, 38(3):63-67,77.
[15]
何大治, 李晓克, 李明明. 考虑视域影响的疏散行为建模及双向行人流仿真[J]. 浙江大学学报(工学版), 2020, 54(6):1185-1193.
[16]
LI S, ZHANG L, WANG Q. A revised social force model considering the velocity difference between pedestrians[C]// 2021 40th Chinese Control Conference (CCC). Shanghai: IEEE, 2021: 6755-6760.
[17]
ZHOU R, CUI Y K, WANG Y, et al. A modified social force model with different categories of pedestrians for subway station evacuation[J]. Tunnelling and Underground Space Technology, 2021, 110: 103837.
[18]
英朋硕. 基于个体特征的天津西南角站换乘设施通行能力研究[D]. 石家庄: 石家庄铁道大学, 2021.
[19]
孙惠芳. 城市轨道交通车站通道行人步行微观参数实测分析[J]. 交通科技与经济, 2017, 19(6):33-38.
[20]
张博思. 典型行李负重对步行疏散速度影响实验研究[J]. 消防科学与技术, 2021, 40(6):837-842.

Accesses

Citation

Detail

段落导航
相关文章

/