AI knowledge model for self-organizing conflict prevention/resolution in close free-flight air space

An artificial intelligence (AI) knowledge model is proposed as a basis for automated conflict management in close free-flight air space. A conceptual framework of the model is developed. The problem of air traffic control (ATC) within a group of potentially conflicting vehicles is represented as an autonomous, self-organizing process. This process incorporates the principles of collective behavior observed in nature (bird flocking, fish schooling, insect swarming, etc.) and comprehensive knowledge of the “pilot vehicle-operational environment” system dynamics derived from special computer experiments. Through this process, real-time knowledge-based predictions of near term flight paths are made to prevent and resolve conflicts in a group of vehicles under normal and demanding conditions. The model may be useful for prototyping intelligent technologies for assisted and automatic collision avoidance in close air space