The paper proposes the solutions for applying the adaptive real-time control algorithms, embedded devices and unmanned aerial vehicles to minimize the risk of collisions in different transport systems. The main goal of the research is to develop the adaptive algorithms for transport control and optimization. The proposed anti-collision system (TACS) is based on artificial immune system concept on the neural network basis with the real-time ability of self-training to detect potentially dangerous states of the system and perform the actions to avoid and prevent crashes caused by collisions of vehicles.
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