Automated Decision Making in Road Traffic Monitoring by On-Board Unmanned Aerial Vehicle System

The study is dedicated to solving the target issues of the ground traffic monitoring aided by the Unmanned Aerial Vehicles (UAV) based on applying the on-board computer vision systems. It has been shown that making decisions on recognizing the occurring traffic situations under the conflicts of functional criteria is a complicated task, affecting considerably the costs associated with elimination of the consequences of such situations. It has been suggested that the classes of the occurring traffic situations should be identified taking into account the necessity to engage the rapid action team of the rescue service. The models have been proposed describing the functional criteria of losses, of the flight safety of the unmanned aerial vehicle and of the class recognition reliability. The issues related to making decisions on recognizing the occurring traffic situations have been considered. The analysis of the strategies to recognize the situation classes have been carried out based on the principles of minimizing the overall losses, on limiting the admissible UAV flight altitude and on ensuring the required class recognition reliability. It has been shown that applying the minimum loss criterion ensures considerable savings of resources under different ratio of the loss quotients.