Development of an Adaptive Evacuation Route Algorithm under Flood Disaster

Flood disaster is often characterized by dangers that strengthen and spread over time (Opasanon S., 2004). Such dynamic situational changes over time might make the shortest route not always the optimal and safest one. From field surveys of real cases such as the Niigata flood disaster in 2004 (Gunma University, 2004; Intensive Heavy Rainfall Disaster Policy Committee, 2004), many people know where the refuge is but they do not know how the situation will progress with certainty and which route is safe under the emergency situation. Static hazard maps may not always help them when an actual disaster happens. Instructions that do not consider the evolution of damage over time and threats of probable additional destruction and deterioration can result in suboptimal decisions that can lead to unnecessarily imposed risk and unnecessarily lost lives (Miller-Hooks and Krauthammer, 2002). In addition, people’s evacuation behaviors such as evacuation time and walking speed also have effect on the optimal strategy. Therefore, in determining the evacuation route, it is important to explicitly consider the time-varying nature of node and people’s reaction to evacuation in such circumstances. It is necessary to provide dynamic information and instructions to help people to make the right decision. As Akagiri Takekazu(2003) mentioned, the future version of hazard maps is to judge flood related various situations such as flow speed, risk index, and for this purpose both inside water and outside water conditions should be analyzed by a simulation model. With such a simulation model used, an advanced version of hazard map should provide dynamic information such as the time the flood will arrive etc. There have already some related research, for example, Cova and Johnson (2003) applied a linear program to address the problem of finding optimal lane-based evacuation routing plans. The primary objective is to minimize the total distance and the secondary objectives is to minimize vehicle merging-conflicts and to prevent crossing-conflicts at intersections. In this research, the constraint method for multi-objective programming was employed. J.MacGregor Smith (1998) proposed a multi-objective model to solve the problem of congestion along the Development of an Adaptive Evacuation Route Algorithm under Flood Disaster