基于元胞鱼群算法的人员疏散模型

针对元胞自动机模型以及原始人工鱼群算法在刻画综合交通枢纽人员常规疏散行为上的局限性，本文提出了一种基于元胞鱼群算法的人员疏散模型，考虑个体之间的行走速度、视野范围差异，将排队机制和出（入）口选择行为、导向行为、记忆功能加入原始人工鱼群算法中，顶层采用改进的人工鱼群算法进行移动位置更新，底层采用元胞自动机模型解决移动位置冲突.实验证明，该模型可真实反映人员在综合交通枢纽内换乘时的疏散过程；在同等环境下，与原始人工鱼群模型相比，该模型实现了个体按照疏散引导进行有序移动，避免了陷入局部最优；与元胞自动机模型相比，其更好地体现了个体的从众、避障和出（入）口选择行为，有效地降低了时间复杂度.

Pedestrian Evacuation Model Based on CA-IAFSA Algorithm

For the limitations of the Cellular Automata (CA) model and the original Artificial Fish Swarm Algorithm (AFSA) in describing the conventional evacuation behavior of the comprehensive transportation hub personnel, a kind of pedestrian evacuation model based on the CA-Improved AFSA (CA-IAFSA) is proposed with considering the difference of walking speed and the difference of view between individuals. As the queuing mechanism and the export (entrance) selection behavior, the guiding behavior, and the memory function are added to the original AFSA. The top layer adopts the IAFSA for mobile location updating, and the bottom layer uses the CA model to solve moving position conflicts. Experiments show that the model can truly reflect the evacuation process of people transferring vehicles in an integrated transportation hub. Under the same environment, compared with the original AFSA, the proposed model realizes the orderly movement of individuals according to guidance, avoiding falling into local optimum. Compared with the CA model, it is better in terms of reflecting the individual''s herd, obstacle avoidance, and export (entrance) selection behavior, thus effectively reduces the time complexity.