A Safety Analysis Process for the Traffic Alert and Collision Avoidance System (TCAS) and See-and-Avoid Systems on Remotely Piloted Vehicles

Kuchar, James K.; Andrews, J.W.; Drumm, A. C.; Hall, Timothy D.; Heinz, Val; Thompson, Steven; Welch, Jerry D.

doi:10.2514/6.2004-6423

Cited by 29 publications

(18 citation statements)

References 5 publications

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“…There are various studies in the literature that use HAS models to evaluate the safety of SAA systems. In their work [8], Maki et al constructed a SAA logic based on the model developed by the Massachusetts Institute of Technology's (MIT) Lincoln Laboratory [9] and Kuchar et al [10] did a rigorous analysis of the TCAS to implement the SAA algorithm for remotely piloted vehicles. In both of these studies, the SAA system was evaluated through simulations in a platform that used MIT's NAS encounter model.…”

mentioning

confidence: 99%

Unmanned Aircraft Systems Airspace Integration: A Game Theoretical Framework for Concept Evaluations

Musavi

Onural

Gunes

et al. 2017

Journal of Guidance, Control, and Dynamics

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The focus of this paper is to present a game theoretical modeling framework for the integration of unmanned aircraft systems into the National Airspace System. The problem of predicting the outcome of complex scenarios, where manned and unmanned air vehicles coexist, is the research problem of this work. The fundamental gap in the literature is that the models of interaction between manned and unmanned vehicles are insufficient: 1) They assume that pilot behavior is known a priori, and 2) They disregard pilot reaction and the decision-making process. The contribution of this paper is to propose a realistic modeling framework that will fill this gap. The foundations of the proposed method are formed by game theory, which investigates strategic decision making between intelligent agents; bounded rationality concept, which is based on the fact that humans cannot always make perfect decisions; and reinforcement learning, which is shown to be effective in human learning in psychology literature. An analysis of integration is conducted using an example scenario in the presence of manned aircraft and fully autonomous unmanned aircraft systems equipped with sense-and-avoid algorithms.Nomenclature m = message P = probability Q = value function for state-action pairs R = minimum safety distance, nm r = relative position vector between the unmanned aircraft system and the intruder, nm r m = minimum relative position vector between the unmanned aircraft system and the intruder, nm r 0 = initial relative position vector between the unmanned aircraft system and the intruder, nm s = state V = value function for states ϵ = learning rate ζ = angle between r and v AB , rad v = velocity vector, m∕s v A = velocity vector of the unmanned aircraft system, m∕s v B = velocity vector of the intruder, m∕s v AB = relative velocity vector between the unmanned aircraft system and the intruder, m∕s v x = X component of the velocity vector, m∕s v y = Y component of the velocity vector, m∕s v d A = velocity adjustment command vector for the unmanned aircraft system, m∕s π· = policy Ψ = heading angle, rad Ψ d = desired heading angle, rad

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mentioning

confidence: 99%

Unmanned Aircraft Systems Airspace Integration: A Game Theoretical Framework for Concept Evaluations

Musavi

Onural

Gunes

et al. 2017

Journal of Guidance, Control, and Dynamics

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“…TCAS [5] is the system responsible for giving warning to pilots about the presence of another aircraft that may present a threat of collision. TCAS relies on a combination of surveillance sensors to collect data on the state of the intruder aircraft and a set of algorithms that determine the best maneuver that the pilot should make to avoid a midair collision.…”

Section: Traffic Collision and Avoidance System (Tcas)mentioning

confidence: 99%

A controlled experiment for the empirical evaluation of safety analysis techniques for safety-critical software

Abdulkhaleq

Wagner

2015

Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering

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Context: Today's safety critical systems are increasingly reliant on software. Software becomes responsible for most of the critical functions of systems. Many different safety analysis techniques have been developed to identify hazards of systems. FTA and FMEA are most commonly used by safety analysts. Recently, STPA has been proposed with the goal to better cope with complex systems including software. Objective: This research aimed at comparing quantitatively these three safety analysis techniques with regard to their effectiveness, applicability, understandability, ease of use and efficiency in identifying software safety requirements at the system level. Method: We conducted a controlled experiment with 21 master and bachelor students applying these three techniques to three safety-critical systems: train door control, anti-lock braking and traffic collision and avoidance. Results: The results showed that there is no statistically significant difference between these techniques in terms of applicability, understandability and ease of use, but a significant difference in terms of effectiveness and efficiency is obtained. Conclusion: We conclude that STPA seems to be an effective method to identify software safety requirements at the system level. In particular, STPA addresses more different software safety requirements than the traditional techniques FTA and FMEA, but STPA needs more time to carry out by safety analysts with little or no prior experience.

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“…In this paper, a collision is defined as an event in which the horizontal separation between two aircraft is less than 100 feet. An NMAC is defined as an event in which the horizontal separation between two aircraft is less than 500 feet [Kuchar et al 2004]. The pre-cursor scenarios are: 1) Before a collision occurs, an NMAC occurs; 2) before an NMAC occurs, two aircraft are on course for an NMAC (an NMAC trajectory); and 3) before two aircraft are on course for an NMAC, they are located at positions that can result in being on course for an NMAC if a blunder occurs.…”

Section: Methodology and Framework To Estimate Collision Probabilitymentioning

confidence: 99%

Methodology for collision risk assessment of an airspace flow corridor concept

Zhang

Shortle

Sherry

2015

Reliability Engineering & System Safety

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A Safety Analysis Process for the Traffic Alert and Collision Avoidance System (TCAS) and See-and-Avoid Systems on Remotely Piloted Vehicles

Cited by 29 publications

References 5 publications

Unmanned Aircraft Systems Airspace Integration: A Game Theoretical Framework for Concept Evaluations

Unmanned Aircraft Systems Airspace Integration: A Game Theoretical Framework for Concept Evaluations

A controlled experiment for the empirical evaluation of safety analysis techniques for safety-critical software

Methodology for collision risk assessment of an airspace flow corridor concept

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