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This paper proposes a novel Forerunner UAV concept to increase the safety of first responders by monitoring the road in front of their emergency ground vehicle (EGV) and notifying the driver about any violation of his/her right of way or approaching danger. The developments are conducted in an R&D project in Hungary. The proposed UAV for the planned urban demonstration is a hexacopter with triple redundant architecture applying a gimbaled camera to monitor the surroundings. In the cooperative control of the EGV and UAV the UAV must fly in front of the EGV which is possible through wireless communication of route data and velocity. Besides the real system a computer simulation representation is also applied including CARLA and Matlab to make exhaustive tests of the system capabilities. Increased attention is devoted to the possible wireless communication solutions as these are safety critical parts of the system. The article ends with the lists of planned simulation and real test scenarios to evaluate the system.

Forerunner UAV refers to an unmanned aerial vehicle equipped with a downward-looking camera flying in front of the advancing emergency ground vehicles (EGV) to notify the driver about the hidden dangers (e.g., other vehicles). A feasibility demonstration in an urban environment having a multicopter as the forerunner UAV and two cars as the emergency and dangerous ground vehicles was done in ZalaZONE Proving Ground, Hungary. After the description of system hardware and software components, test scenarios, object detection and tracking, the main contribution of the paper is the development and evaluation of encounter risk decision methods. First, the basic collision risk evaluation applied in the demonstration is summarized, then the detailed development of an improved method is presented. It starts with the comparison of different velocity and acceleration estimation methods. Then, vehicle motion prediction is conducted, considering estimated data and its uncertainty. The prediction time horizon is determined based on actual EGV speed and so braking time. If the predicted trajectories intersect, then the EGV driver is notified about the danger. Some special relations between EGV and the other vehicle are also handled. Tuning and comparison of basic and improved methods is done based on real data from the demonstration. The improved method can notify the driver longer, identify special relations between the vehicles and it is adaptive considering actual EGV speed and EGV braking characteristics; therefore, it is selected for future application.