Emergency services play an important role in the life of a city and are subject to constant public scrutiny. The efficient dispatch of emergency vehicles (EMVs) requires realistic shortest-path algorithms involving the movement of EMVs within an urban network under emergency conditions. Trip-time estimates used in shortest-path algorithms would be much more precise if it were possible to model more realistically the interactions between EMVs and surrounding traffic, as well as the reactions of other vehicles in the presence of an EMV. Therefore, EMV trajectories should be studied at the microscopic level to accurately model the impact of EMV travel along a path shared with other vehicles. In this research, we develop three models to incorporate specific non-EMV reactions associated with changing lanes, mounting the sidewalk, and approaching an intersection, plus two algorithms to actuate traffic lights at signalized intersections. These models and algorithms were coded in commercial microscopic traffic simulation software through the implementation of an application programming interface (API) designed to overcome the limitations of the software to realistically simulate disturbed traffic conditions and anomalous nonemergency vehicle driver behaviour observed in the presence of an EMV. Basic information about these real-world effects was gleaned from video footage recorded in Santiago, Chile, by traffic cameras, fire truck-mounted cameras, and truck-originated GPS pulses. To validate the design, a real EMV trip captured by the footage was simulated by the API. The simulation considerably reduced the degree of error in delineating the path followed by the EMV compared to the default simulations generated by most commercially available software, thereby demonstrating that the API can provide highly accurate estimates of EMV trip times in an emergency context.