Fuzzy Shared Semi-Autonomous Control System For Military Vehicles

Semi-autonomous control systems applied to automobiles are Advanced Driver Assistance Systems (ADAS) that have gained importance from similar devices with applications in robotics. The control sharing between humans and automatic controllers is the main characteristic of these systems, and can be accomplished through various different manners. However, the use of Artificial Intelligence (AI) techniques for this purpose remains unexplored. In this paper we propose the design of a semi-autonomous control system applied to military vehicles through the use of Fuzzy Inference Systems for the definition of the controller intervention level. Simulations of a vehicle being operated in highly dangerous situations, represented by the existence of hostile military threats or by unexpected maneuvers that could put the stability of the car at risk were performed. The control system’s level of intervention during the simulations was observed, and we could realize the increase of this variable according to the level of threat that the car was exposed to. The application of the proposed system results in safer operation of the vehicle, which shall be controlled with greater influence of the automatic controller when in greater danger. We present a critical analysis of these results and new directions for the future of this work.