The Optimum Design Of The Airborne Collision Avoidance Logic Based On Model

The Traffic Alert and Collision Avoidance System (TCAS) is mandated on all large transport aircraft to reduce air collision risk. Since its introduction, no mid-air collisions between TCAS-equipped aircraft have occurred in the United States. However, General Aviation Corporation aircraft did not install TCAS, or there will be a collision occurred airspace. There is interest in low-cost collision avoidance systems for GA aircraft to reduce collision risk with other GA aircraft as well as with TCAS-equipped aircraft.Since TCAS was designed for large aircraft that can achieve greater vertical rates,the assumptions made by the system and the associated advisories are not always appropriate for GA aircraft. Modifying the TCAS logic to accommodate GA aircraft is far from straightforward. Even minor changes to TCAS to correct operational issues are difficult to implement due to the interaction of the complex rules defining the logic.Firstly, recent work has explored an alternative to the TCAS logic based on optimization with respect to a probabilistic model of aircraft behavior. The model encodes performance constraints of GA aircraft, and a computational technique called dynamic programming allows the optimal collision avoidance strategy to be computed efficiently. This paper also obtained visual logic unit and the real-time flight trajectory through simulating optimization logic that loading to general aviation aircraft and obtained the performance index to estimate the logic unit by reliable Monte Carlo statistic 2 million crash tests.Secondly, the current TCAS logic does not explicitly model variability in pilot response. Instead, it uses a deterministic model to predict the future paths of the aircraft.This paper pursues a more principled approach that uses a probabilistic model to account for pilot response variability. The approach builds upon prior work on framing the collision avoidance problem as a Markov decision process (MDP) and solving for the optimal collision avoidance strategy using dynamic programming (DP). This paper shows that systems that incorporate probabilistic response models are significantly more robust than prior systems that assumed a deterministic response.Finally, if both aircraft are equipped with collision avoidance logic, it is important that the advisories be coordinated to prevent both aircraft from climbing or descending.In this paper, several coordination strategies, both with the optimized logic and the current logic, are evaluated in simulation, and the performance indexes are compared.