Author:
Akira Tsurushima
Affiliation:
Intelligent Systems Laboratory, SECOM CO., LTD., Mitaka, Tokyo, Japan
Keyword(s):
Evolutionary Multi-objective Optimization, Black-box Optimization, Visual Evacuation Signage Assignment Problem, Average Value at Risk, NSGA-II.
Abstract:
Efficient crowd evacuation guidance is crucial but challenging owing to the randomness involved in evacuation
situations and to the unpredictable human behaviors, e.g., herd behavior among evacuees. Many researchers
have found that visual evacuation signage is useful for this purpose, and, thus, evacuation guidance systems
employing visual signage have been developed. A proper arrangement of visual signs on the premises is
necessary to obtain the most out of these attempts; however, several factors make this task challenging, such as
multiple conflicting objectives in the evacuations and randomness and uncertainties in the situation. This study
formulates the visual evacuation signage assignment problem as a stochastic multi-objective optimization
problem and explores the efficient layouts of multiple visual signs on the premises. We consider two objectives
for the efficient layout of visual signs, namely, maximizing the number of evacuees selecting the correct exit
and minimizing th
e total evacuation time. The average value at risk is employed to deal with the risks involved
in noisy objective functions, while the expected values of these objectives are optimized. Pareto-optimal
solutions satisfying both the expected values and the risk measures were explored in cases with one, two and
five evacuation signs using the NSGA-II algorithm.
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