摘要
During a residential settlement evacuation, a large number of individuals do not have access to any private means of transport in order to be evacuated;these people are assembled at Evacuation Assembly Points (E.A.P.s), so as to be picked up, gathered and evacuated by the competent authorities. The present study aims to evaluate whether some pedestrian assembly points are adequate for these people’s fastest assembly, taking into account the demographic characteristics of the studied population and the incline of the studied area’s ground. In order for said fastest assembly and evacuation to be achieved Geographical Information Systems (G.I.S.) and GPS measurements have been employed. The suggested method has led to the creation of the households’ classification maps based upon their inhabitants’ response time in order to improve the pre-existent Intervention Teams’ contingency plans. First, in order to identify the demographic characteristics of the studied population, we have employed the field survey method;second, we have determined the fastest and ergo optimal evacuation routes using the Dijkstra algorithm. What is more, the results hereof prove that it is feasible that the time it takes to gather the pedestrians be optimized by way of choosing the best evacuation point, whilst a method of large crowds’ evacuation in groups has been developed. The latter could constitute a useful tool for Civil Protection Agents and responders.
During a residential settlement evacuation, a large number of individuals do not have access to any private means of transport in order to be evacuated;these people are assembled at Evacuation Assembly Points (E.A.P.s), so as to be picked up, gathered and evacuated by the competent authorities. The present study aims to evaluate whether some pedestrian assembly points are adequate for these people’s fastest assembly, taking into account the demographic characteristics of the studied population and the incline of the studied area’s ground. In order for said fastest assembly and evacuation to be achieved Geographical Information Systems (G.I.S.) and GPS measurements have been employed. The suggested method has led to the creation of the households’ classification maps based upon their inhabitants’ response time in order to improve the pre-existent Intervention Teams’ contingency plans. First, in order to identify the demographic characteristics of the studied population, we have employed the field survey method;second, we have determined the fastest and ergo optimal evacuation routes using the Dijkstra algorithm. What is more, the results hereof prove that it is feasible that the time it takes to gather the pedestrians be optimized by way of choosing the best evacuation point, whilst a method of large crowds’ evacuation in groups has been developed. The latter could constitute a useful tool for Civil Protection Agents and responders.
