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摘要: 突发事件通常具有难以预测、多成因关联、危害性大及演变复杂等特点，应急情况下如何安全高效疏散人员是应急管控领域的重要研究内容.本文将基于人工系统（Artificial systems，A）、计算实验（Computational experiments，C）、平行执行（Parallel excution，P）方法的平行系统理论引入到应急管控领域，提出平行应急疏散系统（Parallel emergency evacuation systems，PeES）基本概念，构建系统体系框架及集成平台，并介绍人工应急疏散系统、计算实验、平行执行等主要功能模块的基本功能及实现方法.通过PeES能实现虚实应急疏散系统的管理与控制、应急方案的实验与评估以及相关人员的学习与培训.最后，以轨道交通枢纽站火灾场景下的乘客应急疏散为典型应用对平行应急疏散系统进行初步验证.Abstract: Emergencies are usually characterized by unpredictable, multi-cause interconnection, great perniciousness, and complicated evolution. How to evacuate personnel safely and efficiently in case of an emergency is an important research content in the field of emergency management and control. This paper proposes the basic concept, framework and integrated platform of parallel emergency evacuation systems (PeES) by introducing the ACP (Artificial systems, Computational experiments, Parallel excution) method based parallel system theory to the field of emergency management and control. The basic functions and implementation methods of main functional modules, including artificial emergency evacuation systems, computational experiments, and parallel execution, are presented. The management and control of artificial and actual systems, experiment and assessment of emergency plans, and study and training of related personnel can be realized through the PeES. Finally, a preliminary verification of the PeES is conducted using the emergency evacuation of passengers in a fire scene at a rail transportation hub station.1) 本文责任编委 张俊
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图 4 基于ACP方法的平行应急疏散系统框架设计思路
Fig. 4 The design idea of ACP-based parallel emergency evacuation systems
图 7 平行应急疏散系统计算实验框架
Fig. 7 Framework of computational experiments in parallel emergency evacuation systems
图 9 轨道交通枢纽站平行应急疏散系统平台:硬件配置(左)和软件平台界面(右)
Fig. 9 Platform of parallel emergency evacuation systems (PeES) for rail transportation hub stations: hardware configurations (left) and the interface of software platform (right)
图 11 疏散开始30 s, 45 s和60 s时2种不同方案下站台乘客疏散快照
Fig. 11 The snapshots of passenger evacuation under different evacuation strategies at the time of 30 s, 45 s and 60 s
图 12 站台剩余乘客数与疏散时间的关系
Fig. 12 Number of passengers in the subway platform against evacuation time under different evacuation strategies
表 1 人员Agent模型默认属性值
Table 1 Default values of individual agent's characteristics
参数 属性 默认值 $m_i$ 质量 80 kg $r_i$ 半径 0.3 m $\tau_i$ 弛豫时间 0.5 s $A_i$ 回避力强度 2 000 N $B_i$ 回避因子 0.08 m $\kappa$ 滑动摩擦因子 $2.4 \times 10^5 {\rm kgm}^{-1} {\rm s}^{-1}$ $k$ 身体压缩因子 $1.2 \times 10^5 {\rm kgm}^{-1}s^{-1}$ $v_i^0$ 期望速度 N$(1.34, 0.26) {\rm ms}^{-1}$ $R_{inf}$ 影响半径 11 m $R_{vf}$ 视野半径 10 m $\beta_i$ 愿意跟随程度 1 $a_i$ 引导信息可得度 1 $b_1$ 位置反馈因子 0.05 $b_2$ 速度反馈因子 0.05 $\lambda _i$ 各向异性 0.5 
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表 2 乘客应急疏散计算实验结果(s)
Table 2 Experimental results of passenger emergency evacuation (s)
对照方案 方案1 方案2 单次疏散时间 146 87 81 平均疏散时间 143.2 92.5 80.8 标准差 28.4 8.2 5.5
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