A Novel Emergency Vehicle Scheduling Model to deal with Dynamic City Conditions

To improve emergency response efficiency under uncertainty, an urban emergency vehicle scheduling model is optimized by mathematical planning. The existing scheduling models are only built in accordance with current incidents while ignoring future incidents. To deal efficiently with future incidents, we adopt a different and novel approach in this paper by establishing a mathematical model which minimizes the overall response time cost with weights as the objective function. In terms of time and space constraints, the travel time calculation of the emergency vehicle is considered under different traffic flow conditions. Case results show that if the potential incidents really occur, the overall response time cost will be minimized by the scheduling policy. Furthermore, the selection of the confidence level determines the degree of system's emphasis on future events. Dealing with future serious incidents would be focused on prevention as the confidence level tends to one, while current incidents would be responded to with a priority as confidence level tends to zero.