Abstract: To reduce the time cost of manual design of the Building Information Modeling (BIM) fire evacuation routes and to enhance design efficiency, an improved algorithm was proposed based on Deep Q Learning (DQN) and A* algorithm, through which a BIM evacuation design automation tool developed. First, the evacuation path of the room was drawn by A* algorithm. Then, the path from the evacuation door to safety exit in floor evacuation was determined using the improved DQN algorithm, and was drawn by A* algorithm. On the basis of the DQN algorithm, we redesigned reward matrix assignment and added reward matrix verification to improve the correctness of floor evacuation. Finally, we applied the improved algorithm-based evacuation design automation tool to practical projects. The results show that this improved algorithm can not only draw the route correctly, but also increase the efficiency by 2 to 3 times compared with manual drawing. The efficiency of this algorithm can be further improved by server deployment and hardware upgrades. At present, the automatic design tool has been adopted in several actual projects of Shanghai Digital Architecture Fabrication Technology Center (SFAB), Tongji Architectural Design (Group) Co., Ltd. 

Key words: artificial intelligence, building information modeling, evacuation, design automation, deep Q-learning