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An efficient strategy for warning dissemination in crowds during emergencies

Shuangyan Wang,Yun-feng Deng,Ying Li

Published 2020 in International journal of disaster risk reduction

ABSTRACT

Abstract In emergencies, warnings can flow amongst crowds via person-to-person communications. Interpersonal warning dissemination is important for warning people when the government does not have sufficient time or personnel to notify all affected people. Moreover, if interpersonal warning dissemination can be used to warn people in emergencies, the warning efficiency of the crowd can be improved so that the emergency response efficiency of people can be improved. Similarly, anti-warnings that can cause a negative influence on emergency responses can also flow amongst crowds. In this scenario, how can interpersonal dissemination be properly utilized to improve warning efficiency? In this paper, we build a game model that includes warning and anti-warning dissemination based on multi-agent modelling. Moreover, we propose an efficient strategy based on dynamic dissemination characteristics for improving warning efficiency in a crowd. To ensure the reliability of the game model, the Monte Carlo method is applied to conduct our experiments. To verify the practicability of the proposed strategy, 40 Monte Carlo experiments are conducted in synthetic and real crowds. The experimental results demonstrate the effectiveness of our proposed strategy. The proposed game model can be applied to study the dissemination of information in a crowd during emergencies. The proposed strategy can be used to train people in emergency drills to improve their emergency response capabilities.

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