Name
Abstract | ||
|---|---|---|
Safety planning for crowd evacuation is an important and active research topic nowadays. One important issue is to devise the evacuation plans of individuals in emergency situations so as to reduce the total evacuation time. This paper proposes a novel evolutionary algorithm (EA)-based methodology, together with agent-based crowd simulation, to solve the evacuation planning problem. The proposed method features a novel segmentation strategy which divides the entire evacuation region into sub-regions based on a discriminant function. Each sub-region is assigned with an exit gate, and individuals in a sub-region will run toward the corresponding exit gate for evacuation. In this way, the evacuation planning problem is converted to a symbolic regression problem. Then an evolutionary algorithm, using agent-based crowd simulation as fitness function, is developed to search for the global optimal solution. The simulation results on different scenarios demonstrate that the proposed method is effective to reduce the evacuation time. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/WSC.2014.7019906 | Winter Simulation Conference |
Keywords | Field | DocType |
symbolic regression problem,fitness function,evolutionary algorithm,evolutionary computation,ea,regression analysis,emergency situations,emergency management,discriminant function,safety planning,segmentation strategy,evacuation planning problem,planning,agent-based crowd simulation | Evolutionary algorithm,Simulation,Computer science,Segmentation,Crowd evacuation,Fitness function,Crowd simulation,Artificial intelligence,Symbolic regression,Discriminant function analysis | Conference |
ISBN | Citations | PageRank |
978-1-4673-9741-4 | 5 | 0.44 |
References | Authors | |
15 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing-hui Zhong | 1 | 380 | 33.00 |
| Wentong Cai | 2 | 1928 | 197.81 |
| Lin-bo Luo | 3 | 189 | 15.97 |
| Michael Lees | 4 | 58 | 6.48 |