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Collision avoidance system optimization with probabilistic pilot response models

Published in:
2011 American Control Conf., 29 June-1 July 2011, pp. 2765-2770.

Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. Uncertainty in the compliance of pilots to advisories makes designing collision avoidance logic challenging. Prior work has investigated formulating the problem as a Markov decision process and solving for the optimal collision avoidance strategy using dynamic programming. The logic was optimized to a pilot response model in which the pilot responds deterministically to all alerts. Deviation from this model during flight can degrade safety. This paper extends the methodology to include probabilistic pilot response models that capture the variability in pilot behavior in order to enhance robustness.
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Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. Uncertainty in the compliance of pilots to advisories makes designing collision avoidance logic challenging. Prior work has investigated formulating the problem as a Markov...

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Unmanned aircraft collision avoidance using continuous-state POMDPs

Published in:
2011 Robotics: Science and Systems, 27-30 June 2011.

Summary

An effective collision avoidance system for unmanned aircraft will enable them to fly in civil airspace and greatly expand their applications. One promising approach is to model aircraft collision avoidance as a partially observable Markov decision process (POMDP) and automatically generate the threat resolution logic for the collision avoidance system by solving the POMDP model. However, existing discrete-state POMDP algorithms cannot cope with the high-dimensional state space in collision avoidance POMDPs. Using a recently developed algorithm called Monte Carlo Value Iteration (MCVI), we constructed several continuous-state POMDP models and solved them directly, without discretizing the state space. Simulation results show that our 3-D continuous-state models reduce the collision risk by up to 70 times, compared with earlier 2-D discrete-state POMDP models. The success demonstrates both the benefits of continuous-state POMDP models for collision avoidance systems and the latest algorithmic progress in solving these complex models.
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Summary

An effective collision avoidance system for unmanned aircraft will enable them to fly in civil airspace and greatly expand their applications. One promising approach is to model aircraft collision avoidance as a partially observable Markov decision process (POMDP) and automatically generate the threat resolution logic for the collision avoidance system...

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Analytical workload model for estimating en route sector capacity in convective weather

Published in:
9th USA/Europe Air Traffic Management Research and Development Sem., ATM 2011, 14-17 June 2011.

Summary

We have extended an analytical workload model for estimating en route sector capacity to include the impact of convective weather. We use historical weather avoidance data to characterize weather blockage, which affects the sector workload in three ways: (1) Increase in the conflict resolution task rate via reduction in available airspace, (2) increase in the recurring task load through the rerouting of aircraft around weather, and (3) increase in the inter-sector coordination rate via reduction in the mean sector transit time. Application of the extended model to observed and forecast data shows promise for future use in network flow models.
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Summary

We have extended an analytical workload model for estimating en route sector capacity to include the impact of convective weather. We use historical weather avoidance data to characterize weather blockage, which affects the sector workload in three ways: (1) Increase in the conflict resolution task rate via reduction in available...

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A new approach for designing safer collision avoidance systems

Published in:
9th USA/Europe Air Traffic Management Research and Development Sem., ATM 2011, 14-17 June 2011.

Summary

The Traffic Alert and Collision Avoidance System (TCAS) has been shown to significantly reduce the risk of mid-air collision and is currently mandated worldwide on all large transport aircraft. Engineering the collision avoidance logic was a very costly undertaking that spanned several decades. The development followed an iterative process where the logic was specified using pseudocode, evaluated on encounters in simulation, and revised based on performance against a set of metrics. Modifying the logic to get the desired behavior is difficult because the pseudocode contains many heuristic rules that interact with each other in complex ways. Over the years, the TCAS logic has become challenging to maintain. With the anticipated introduction of next-generation air traffic control procedures and surveillance systems, the logic will require significant revision to prevent unnecessary alerts. Recent work has explored a new approach for designing collision avoidance systems that has the potential to shorten the development cycle, improve maintainability, and enhance safety with fewer false alerts. The approach involves leveraging recent advances in computation to automatically derive optimized collision avoidance logic directly from encounter models and performance metrics. This paper outlines the general approach and discusses the anticipated impact on development, safety, and operation.
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Summary

The Traffic Alert and Collision Avoidance System (TCAS) has been shown to significantly reduce the risk of mid-air collision and is currently mandated worldwide on all large transport aircraft. Engineering the collision avoidance logic was a very costly undertaking that spanned several decades. The development followed an iterative process where...

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Establishing a risk-based separation standard for unmanned aircraft self separation

Published in:
9th USA/Europe Air Traffic Management Research and Development Sem., ATM 2011, 14-17 June 2011.

Summary

Unmanned Aircraft Systems require an ability to sense and avoid other air traffic to gain access to civil airspace and meet requirements in civil aviation regulations. One sense and avoid function is self separation, which requires that aircraft remain "well clear." An approach is proposed in this paper to treat well clear as a separation standard, thus posing it as a relative state between aircraft where the risk of collision first reaches an unacceptable level. By this approach, an analytically-derived boundary for well clear can be derived that supports rigorous safety assessment. A preliminary boundary is proposed in both time and distance for the well clear separation standard, and recommendations for future work are made.
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Summary

Unmanned Aircraft Systems require an ability to sense and avoid other air traffic to gain access to civil airspace and meet requirements in civil aviation regulations. One sense and avoid function is self separation, which requires that aircraft remain "well clear." An approach is proposed in this paper to treat...

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A space-time multiscale analysis system: a sequential variational analysis approach

Published in:
Monthly Weather Rev., Vol. 139, No. 4, April 2011, pp. 1224-1240.

Summary

As new observation systems are developed and deployed, new and presumably more precise information is becoming available for weather forecasting and climate monitoring. To take advantage of these new observations, it is desirable to have schemes to accurately retrieve the information before statistical analyses are performed so that statistical computation can be more effectively used where it is needed most. The authors propose a sequential variational approach that possesses advantages of both a standard statistical analysis [such as with a three-dimensional variational data assimilation (3DVAR) or Kalman filter] and a traditional objective analysis (such as the Barnes analysis). The sequential variational analysis is multiscale, inhomogeneous, anisotropic, and temporally consistent, as shown by an idealized test case and observational datasets in this study. The real data cases include applications in two-dimensional and three-dimensional space and time for storm outflow boundary detection (surface application) and hurricane data assimilation (three-dimensional space application). Implemented using a multigrid technique, this sequential variational approach is a very efficient data assimilation method.
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Summary

As new observation systems are developed and deployed, new and presumably more precise information is becoming available for weather forecasting and climate monitoring. To take advantage of these new observations, it is desirable to have schemes to accurately retrieve the information before statistical analyses are performed so that statistical computation...

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Triangle TCAS antenna

Published in:
MIT Lincoln Laboratory Report ATC-380

Summary

The Traffic Alert and Collision Avoidance (TCAS) provides a pilot display showing the range and bearing of nearby aircraft. TCAS obtains the bearing information by using an angle-of-arrival antenna. In the development of TCAS at Lincoln Laboratory, the first airborne tests were conducted using an Adcock antenna, which is a small square array of four monopole elements. This report describes an alternative antenna for TCAS, using three elements in the shape of a triangle. It is shown that the triangle antenna is less sensitive to receiver noise, and that improvement factor is about 10 dB.
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Summary

The Traffic Alert and Collision Avoidance (TCAS) provides a pilot display showing the range and bearing of nearby aircraft. TCAS obtains the bearing information by using an angle-of-arrival antenna. In the development of TCAS at Lincoln Laboratory, the first airborne tests were conducted using an Adcock antenna, which is a...

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Partially-controlled Markov decision processes for collision avoidance systems

Published in:
ICAART 2011, Proc. of the 2rd Int. Conf. on Agents and Artificial Intelligence, 28-30 January 2011, pp. 61-70.

Summary

Deciding when and how to avoid collision in stochastic environments requires accounting for the likelihood and relative costs of future sequences of outcomes in response to different sequences of actions. Prior work has investigated formulating the problem as a Markov decision process, discretizing the state space, and solving for the optimal strategy using dynamic programming. Experiments have shown that such an approach can be very effective, but scaling to higher-dimensional problems can be challenging due to the exponential growth of the discrete state space. This paper presents an approach that can greatly reduce the complexity of computing the optimal strategy in problems where only some of the dimensions of the problem are controllable. The approach is demonstrated on an airborne collision avoidance problem where the system must recommend maneuvers to an imperfect pilot.
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Summary

Deciding when and how to avoid collision in stochastic environments requires accounting for the likelihood and relative costs of future sequences of outcomes in response to different sequences of actions. Prior work has investigated formulating the problem as a Markov decision process, discretizing the state space, and solving for the...

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Aircraft collision avoidance using Monte Carlo real-time belief space search

Published in:
J. Intell. Robot. Syst., Vol. 64, No. 2, 2011, pp. 277-98.

Summary

The aircraft collision avoidance problem can be formulated using a decision-theoretic planning framework where the optimal behavior requires balancing the competing objectives of avoiding collision and adhering to a flight plan. Due to noise in the sensor measurements and the stochasticity of intruder state trajectories, a natural representation of the problem is as a partially-observable Markov decision process (POMDP), where the underlying state of the system is Markovian and the observations depend probabilistically on the state. Many algorithms for finding approximate solutions to POMDPs exist in the literature, but they typically require discretization of the state and observation spaces. This paper investigates the introduction of a sample-based representation of state uncertainty to an existing algorithm called Real-Time Belief Space Search (RTBSS), which leverages branch-and-bound pruning to make searching the belief space for the optimal action more efficient. The resulting algorithm, called Monte Carlo Real-Time Belief Space Search (MC-RTBSS), is demonstrated on encounter scenarios in simulation using a beacon-based surveillance system and a probabilistic intruder model derived from recorded radar data.
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Summary

The aircraft collision avoidance problem can be formulated using a decision-theoretic planning framework where the optimal behavior requires balancing the competing objectives of avoiding collision and adhering to a flight plan. Due to noise in the sensor measurements and the stochasticity of intruder state trajectories, a natural representation of the...

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Robust airborne collision avoidance through dynamic programming

Published in:
MIT Lincoln Laboratory Report ATC-371

Summary

The Traffic Alert and Collision Avoidance System (TCAS) uses an on-board beacon radar to monitor the local air traffic and logic to determine when to alert pilots to potential conflict. The current TCAS logic was the result of many years of development and involved the careful engineering of many heuristic rules specified in pseudocode. Unfortunately, due to the complexity of the logic, it is difficult to revise the pseudocode to accommodate the evolution of the airspace and the introduction of new technologies and procedures. This report summarizes recent advances in computational techniques for automatically deriving the optimal logic with respect to a probabilistic model and a set of performance metrics. Simulations demonstrate how this new approach results in logic that significantly outperforms TCAS according to the standard safety and operational performance metrics.
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Summary

The Traffic Alert and Collision Avoidance System (TCAS) uses an on-board beacon radar to monitor the local air traffic and logic to determine when to alert pilots to potential conflict. The current TCAS logic was the result of many years of development and involved the careful engineering of many heuristic...

READ MORE