## 2 The Current Approach  
The current approach to the problem of firefighting vehicles throughput, route planning, or effective arrival times focuses primarily on the routes between the fire station and the general area near the location of the fire. Several scientific publications have dealt with this topic, and several of them are summarised in the following paragraphs. Notable is a publication from the city of Changsha (China) [8; 9] that is addressing the arrival times of firefighting units within the city. The premise in this study is that at least one fire tanker and one fire ladder truck should arrive at a given location within 240 s of a fire being detected. However, problems caused by congestion and a low density of fire stations in city centres make this assumption very difficult. A similar approach was applied in the city of Nanjing (China) [10] in a study to verify the accessibility of different parts of the city in relation to the effective travel times of existing fire stations. The assessment of the suitability of fire station locations and their time of accessibility to the fire scene was analysed using the FC2 SFCA method, which focuses on specifically defining the service boundary from each fire station and determining from which stations it is appropriate to lead the response to different parts of the city. The paper furthermore describes the comparison of the previously mentioned method with the older E2 SFCA method and assesses the differences and precision of each procedure. The method shows that the coverage near fire stations or in the city peripheries is far more effective than coverage in the city centre, where high traffic density is a particular problem. Publications from Pennsylvania State University (USA) [11] discuss the arrival times to the location of an incident together with a main focus on the impacts and economic losses associated with the time lost by the emergency services in reaching the fire location due to traffic congestion. Other research related to integrated emergency services [12] is concerned with improving the efficiency of passage through light-controlled intersections, where emergency vehicles share their positional information with traffic lights. Research conducted in Saudi Arabia uses a mobile application that links the vehicle data with map data and the traffic light sensors. In the event that an IRS vehicle arrives at a traffic light, the vehicle's lane switch to the clear phase. In this way, traffic from other traffic directions does not accumulate at the crossroads and the traffic flow is smooth, without significant delays. Research at Bangladesh University [13] focused on dynamic changes in the signal depending on the current position of the IRS vehicles. The proposed system works on a cloud centric Internet of Things (IoT) principle. It collects information about the location of vehicles and signals at traffic-light-controlled crossroads. The acquired information is evaluated, and the system subsequently changes the phases on the traffic lights to enable a priority pass-through of the IRS vehicles. Another research study was trying to achieve similar results by solving crossing problems using a complex RFID-based system [14]. The system is designed to be able to detect both image and sound from the IRS vehicles and thus be able to change the order of phases at light-controlled intersections. This enables to the IRS vehicles an easier crossing of these incriminated points. The research projects also aim to address the interaction between vehicles and their environment. A paper published by the University of Zilina (Slovakia) [15] presentscooperation between individual vehicles and sensor data, helping to increase the safety and improve the communication skills of individual road users. The use of vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) methods is intended to help warn drivers of approaching emergency services in time to create space for mutually safe crossing.