A self-organizational approach for resolving air traffic conflicts
The Lincoln Laboratory Journal - Special issue on air traffic control
Automatic aircraft conflict resolution using genetic algorithms
SAC '96 Proceedings of the 1996 ACM symposium on Applied Computing
Neural Nets Trained by Genetic Algorithms for Collision Avoidance
Applied Intelligence
PVS: A Prototype Verification System
CADE-11 Proceedings of the 11th International Conference on Automated Deduction: Automated Deduction
A review of conflict detection and resolution modeling methods
IEEE Transactions on Intelligent Transportation Systems
PETRI NETS '08 Proceedings of the 29th international conference on Applications and Theory of Petri Nets
A flexible and extensible architecture for experimental model validation
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
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New air traffic management concepts distribute the responsibility for traffic separation among the several actors of the aerospace system. As a consequence, these concepts move the safety risk from human controllers to the onboard software and hardware systems. One example of the new kind of distributed systems is air traffic conflict detection and resolution. Traditional methods for safety analysis such as human-in-the-loop simulations, testing, and flight experiments may not be sufficient in this highly distributed system: the set of possible scenarios is too large to have a reasonable coverage. This paper proposes a paradigm shift for the safety analysis of avionics systems where formal methods drive the development of critical systems. As a case study of this approach, we report the mechanical verification of an algorithm for air traffic conflict resolution and recovery.