Name
Abstract | ||
|---|---|---|
When the occupant density of buildings is large enough, evacuees are prone to congestion during emergency evacuation, which leads to the extension of the overall escape time. Especially for multi-exit buildings, it's a challenging problem to afford an effective evacuation plan. In this paper, a novel evacuation planning algorithm applied to multi-exit buildings is proposed, which is based on an indoor route network model. Firstly, evacuees are grouped by their location proximity, then all groups are approximately equally classified into several evacuation zones, each of which has only one safe exit. After that, all evacuation groups in the same zone are sorted by their shortest path length, then the time window of each evacuation group occupying the safe exit is calculated in turn. In the case of congestion at the safe exit, the departure time of each evacuation group is delayed in its arrival order. The objectives of the proposed algorithm include minimizing the total evacuation time of all evacuees, the travel time of each evacuee, avoiding traffic congestion, balancing traffic loads among different exits, and achieving high computational efficiency. Case studies are conducted to examine the performance of our algorithm. The influences of group number, group size, evacuation speed on the total evacuation time are discussed on a single-exit network, and that of partitioning methods and evacuation density on the performance and applicability in different congestion levels are also discussed on a multi-exit network. Results demonstrate that our algorithm has a higher efficiency and performs better for evacuations with a large occupant density. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.3390/ijgi9010046 | ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION |
Keywords | Field | DocType |
emergency evacuation,indoor route network,multi-exit buildings,staged evacuation,congestion | Evacuation plan,Shortest path problem,Emergency evacuation,Planning algorithms,Computer science,Operations research,Travel time,Network model,Traffic congestion | Journal |
Volume | Issue | Citations |
9 | 1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Litao Han | 1 | 1 | 1.40 |
| Huan Guo | 2 | 0 | 0.34 |
| Haisi Zhang | 3 | 0 | 0.34 |
| Qiaoli Kong | 4 | 2 | 1.76 |
| Aiguo Zhang | 5 | 0 | 0.68 |
| Cheng Gong | 6 | 0 | 1.01 |