When a large-scale disaster occurs, evacuees have to evacuate to safe places quickly. For this purpose, an automatic evacuation guiding scheme based on cooperation between evacuees and their mobile nodes has been proposed. The previous work adopts a shortest-distance based route selection and does not consider the impact of traffic congestion caused by evacuation guiding. In this thesis, we examine the effectiveness of a congestion-aware route selection for the automatic evacuation guiding. We first adopt a traffic congestion model where each evacuee's moving speed on a road is determined by the population density of the road and his/her order among evacuees traveling in the same direction. Based on this congestion model, each evacuee's mobile node estimates the cost, i.e., traveling time, of each road in the area. Each mobile node collects information about blocked road segments and positions of other evacuees through communication infrastructures or other mobile nodes. Based on the obtained information, it calculates and selects the smallest-cost route. Through simulation experiments, we show that the congestion-aware route selection can reduce both average and maximum evacuation times compared to the shortest-distance based route selection, especially under highly congested situations. Furthermore, we show that the congestion-aware route selection can work well even under highly damaged situations where only direct wireless communication among mobile nodes is only available.