Evacuation information methodology that combined a flooded environment and pedestrian behavioral model

Disaster information influences decision-making. Wireless internet and location-based services, aided by recent technological advances, have laid the foundation for providing personalized disaster information. Despite the provision of simple disaster forecasts and warnings, provision of specific evacuation actions (“where” and “how,” i.e., location and reachability of safe areas) and location-based personalized information that consider real-time disaster situations are a pressing priority. Thus, this study proposed and developed a three-step methodology for providing disaster information during floods that combined a flooded environment and pedestrian behavioral model, namely, 1) prediction of the flooded environment, 2) analysis of evacuation routes based on the movement time of evacuees according to the flood depth, and 3) provision of evacuation information by selecting the optimal evacuation route. This model was demonstrated in the Gangnam Station area in Seoul, Korea. Flooded environment prediction modeling of the target area was performed by applying the 100-year rainfall design to the Storm Water Management Model. The optimal evacuation route, according to the flood depth, was selected by applying the behavioral model (movement time calculation formula) for each evacuee derived through an evacuation behavior experiment. The pre- and post-flooding age- and gender-wise total evacuation distance and time were compared and analyzed. Post-flooding, the evacuation distance and time increased by 168.3% (381.34 m) and 172.3% (3.16 min) on average, respectively, indicating that evacuees must travel farther and longer. The analysis of post-flooding evacuation route change types revealed changes in evacuation distance and time in cases where shelters and evacuation routes and time were significantly different depending on evacuee characteristics (age and gender). This indicated that specific and visual disaster information can be provided according to evacuees’ age and gender using the proposed methodology. This study can serve as the basis for designing an advanced and personalized disaster information system that can provide specific evacuation actions to aid fast evacuation decision-making during floods.