Abstract
In order to find the optimal path for emergency evacuation, this paper proposes a dynamic path optimization algorithm based on real-time information to search the optimal path and it takes fire accident as an example to introduce the algorithm principle. Before the accidents, it uses the Dijkstra algorithm to get the prior evacuation network which includes evacuation paths from each node to the exit port. When the accidents occur, the evacuees are unable to pass through the passage where the accident point and the blocking point are located, then the proposed method uses the breadth-first search strategy to solve the path optimization problem based on the prior evacuation network, and it dynamically updates the evacuation path according to the real-time information. Because the prior evacuation network includes global optimal evacuation paths from each node to the exit port, the breadth-first search algorithm only searches local optimal paths to avoid the blockage node or dangerous area. Because the online optimization solves a local pathfinding problem and the entire topology optimization is an offline calculation, the proposed method can find the optimal path in a short time when the accident situation changes. The simulation tests the performances of the proposed algorithm with different situations based on the topology of a building, and the results show that the proposed algorithm is effective to get the optimal path in a short time when it faces changes caused by the factors such as evacuee size, people distribution, blockage location, and accident points.
Highlights
Effective emergency evacuation paths are important for the safety of personal in accidents, and the basic requirement is that the commander gets the optimal paths to fit the dynamic changes in a short time. is paper proposes a dynamic path optimization method which includes offline search and online search. e offline optimization gets the prior evacuation network which includes evacuation paths from each node to the exit port, and the online optimization searches the local optimal paths based on the prior evacuation network when the accidents happen. e changes from accident locations, dangerous areas, and blocking paths call the online optimization algorithm to search the dynamic optimal paths
Evacuation Environment Model e emergency evacuation model mainly includes microscopic model and macroscopic model [45]. e microscopic model focuses on the study of individual behavior characteristics, and the path optimization algorithm simulates human individual behavior and mental activities to select evacuation paths
Because the microscopic model uses less overall information about the environment, it always gets local feasible paths and ignores the global optimal paths. e local feasible paths are able to guide people to move toward the exit, but it is different from the optimal solution that considers the evacuation time and personal safety during the evacuation process
Summary
With prior information of the evacuation model shown, the offline optimization is used to search for the optimal paths that contain evacuation routes from each node to exit nodes. Is search is an offline process that uses the Dijkstra algorithm to get the prior evacuation path network that stores the node number of each evacuation path. If people are at node N3, they will use the information shown in Table 2 to quickly escape to the safety exit, so this network is the prior information for the people to escape.
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