Conflating qualitative and quantitative criteria using spatial models for emergency vehicle routing in urban environments

Urbanemergency vehicles, due tosensitivity oftheir mission, are alwayslooking forthe shortest timeto reach the destination. In great cities, in addition todistance, several factors and parameters, with respect to complexity and extent of thetransport andtraffic, are influencing on time of arrival of an emergency vehicle, some of the parameters are qualitative or quantitative, dynamic or static. In this paper, the modern approach used is based on composing conflation models, Gamma quantification methods, travel time prediction formulas and metaheuristic algorithms in order to find most optimal route. In this paper, first we have tried to introduce all the calculated, available, qualitative and quantitative, affecting factors related to emergency routing, thenwith converting qualitative parameters to quantitative one, normalize each parameter by the maximum approach and conflate them in such a way that thepriority and impact of each parameteris determined to find the optimal route.In order to calculating the priority and impact of factors, the Gamma test method, as a data derived method is selected. The procedure implemented by use of road network and traffic volume data from two regions of Tehran. Based on this approach, the considered weights for each following criterion of degree of difficulty including quality, width, slope, category and route directness are 0.331, 0.286, 0.188, 0.172 and 0.020, respectively. Finally, genetic meta-heuristic algorithm is used to select the optimal route and the results compared with common Dijkstra routing algorithm. The length of the selected route by GA is about 130 meters in one time and about 300 meter in the other time more than the selected one by Dijkstra algorithm. Based on the implemented comparison, the represented approach in this paper had a considerable superiority than the simple current methods.