Mobile-Cloud Evacuation Guiding for Large-Scale Disasters

In the 2011 Great East Japan Earthquake, both fixed and mobile communication networks had not been available for a long time and/or in wide areas, due to damage to communication infrastructures. As a result, it has been reported that disaster victims and rescuers could not smoothly collect and distribute important information, e.g., safety information, evacuation information, and government information, even though they carried their own mobile nodes, e.g., cellular phones and smart phones.

When disasters occur, disaster victims quickly have to evacuate to near safety places to keep their own safety. Under such situations, it is necessary to grasp the following information: safety places and safe routes to those places. Although they can acquire static information, e.g., map and locations of safety places, in usual time, they cannot grasp dynamic information, e.g., damage situations in disaster areas.

Quickly grasping damage situations will help evacuees to determine actions for evacuation, but it is not necessarily easy to grasp the damage situations, e.g., outbreak of fire, collapse of buildings, flood, and cracks in the ground. It is possible to detect the damage situations by cameras and/or various types of sensors, but it has a potential drawback of restriction of coverage area and breakdown of both such devices and/or communication infrastructures. Therefore, the larger the disaster scale is, the more difficult it is for public institutions to quickly investigate damage situations and to distribute such emergency information to the evacuees.

In this project, we try to establish an automatic evacuation guiding scheme using evacuees’ mobile nodes, which can automatically grasp damage situations and guide evacuees. Evacuees can obtain the surrounding map and locations of safety places by preinstalling applications for evacuation guiding in their mobile nodes. When disasters occur, the applications calculate evacuation routes with these local information and navigate the evacuees using the routes. In addition, the applications can also grasp the actual evacuation routes of the evacuees, i.e., their trajectories, by measuring their positions periodically. With the help of the interaction between evacuation guiding by mobile nodes and evacuees’ actual evacuations, the applications can automatically estimate blocked road segments and recalculate evacuation routes by using the estimated information of the blocked road segments.