Most of the existing staged evacuation algorithms only consider the impact of crowd density on evacuation partition, but do not take into account the influence of the spatial distribution of occupants and the capacity of exits on the total evacuation time (TET). Therefore, a novel indoor emergency evacuation algorithm based on time equalization is proposed in this paper. All factors affecting TET such as the position and size of each group and the capacity of exits are fully considered in the proposed algorithm, which are uniformly converted into the occupancy time of each exit. An improved Dijkstra algorithm is used to generate evacuation zones according to the proximity relationship and the occupancy time of different exits. The strategy of waiting at the starting point is adopted to ensure that all evacuees are free from congestion during the escape process. In addition, the method of group merging is proposed to further increase the balance among all zones during the partitioning process. The objectives of the proposed algorithm include minimizing the TET of all evacuees, the path length of each escape group, avoiding congestion during the escape process. The experimental results show that the proposed algorithm effectively reduces TET and the path length of groups compared with existing algorithms, which improves the efficiency of evacuation and utilization of all exits and can be applied to the various distribution and density of evacuees.

中文翻译：

---

一种基于时间均衡的多区域分级室内应急疏散算法

现有的分阶段疏散算法大多只考虑人群密度对疏散分区的影响，而没有考虑人员空间分布和出口通行能力对总疏散时间（TET）的影响。因此，本文提出了一种基于时间均衡的新型室内应急疏散算法。该算法充分考虑了各组的位置、大小、出口容量等影响TET的所有因素，统一换算为各出口的占用时间。使用改进的 Dijkstra 算法根据邻近关系和不同出口的占用时间生成疏散区。采用起点等待策略，确保所有撤离人员在撤离过程中不发生拥堵。此外，还提出了组合并的方法，以进一步增加分区过程中所有区域之间的平衡。所提出算法的目标包括最小化所有疏散人员的TET、每个逃生组的路径长度、避免逃生过程中的拥塞。实验结果表明，与现有算法相比，该算法有效降低了TET和群体路径长度，提高了所有出口的疏散和利用效率，可适用于疏散人员的各种分布和密度。提出了组合并的方法，以进一步增加分区过程中所有区域之间的平衡。所提出算法的目标包括最小化所有疏散人员的TET、每个逃生组的路径长度、避免逃生过程中的拥塞。实验结果表明，与现有算法相比，该算法有效降低了TET和群体路径长度，提高了所有出口的疏散和利用效率，可适用于疏散人员的各种分布和密度。提出了组合并的方法，以进一步增加分区过程中所有区域之间的平衡。所提出算法的目标包括最小化所有疏散人员的TET、每个逃生组的路径长度、避免逃生过程中的拥塞。实验结果表明，与现有算法相比，该算法有效降低了TET和群体路径长度，提高了所有出口的疏散和利用效率，可适用于疏散人员的各种分布和密度。