Analysis of resident evacuation behavior during heavy rain disasters by applying image recognition technology to questionnaire survey data

Abstract

Although resident evacuation behavior has been analyzed from various perspectives, the number of casualties due to heavy rain disasters continues to increase. Therefore, it is still difficult to say that the issues related to resident evacuation have been resolved. As a new attempt, the authors attempted to use XAI (Explainable AI) to analyze the factors behind resident evacuation behavior, but there are still issues with the predictive accuracy of the behavior model.

In this study, questionnaire survey data on resident evacuation behavior during heavy rain disasters was converted into image data and XAI (Explainable AI) was applied to image recognition technology. As a result, the predictive accuracy of the resident evacuation behavior model was improved. In addition to having experience of disaster before a disaster, we showed that obtaining appropriate evacuation information during a disaster and damage to one’s home affect evacuation behavior.