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A new approach for designing safer collision avoidance systems

June 14, 2011
  |
Conference Paper
Author:
Mykel J. Kochenderfer
…
Published in:
9th USA/Europe Air Traffic Management Research and Development Sem., ATM 2011, 14-17 June 2011.
Topic:
collision avoidance
R&D area:
R&D group:

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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A new approach for designing safer collision avoidance systems

Partially-controlled Markov decision processes for collision avoidance systems

January 28, 2011
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Conference Paper
Author:
Mykel J. Kochenderfer
…
Published in:
ICAART 2011, Proc. of the 2rd Int. Conf. on Agents and Artificial Intelligence, 28-30 January 2011, pp. 61-70.
Topic:
air traffic control
R&D area:
R&D group:

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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Partially-controlled Markov decision processes for collision avoidance systems

Robust airborne collision avoidance through dynamic programming

January 3, 2011
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Project Report
Author:
Mykel J. Kochenderfer
…
Published in:
MIT Lincoln Laboratory Report ATC-371
Topic:
collision avoidance
R&D area:
R&D group:

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...

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Robust airborne collision avoidance through dynamic programming

Robustness of optimized collision avoidance logic to modeling errors

October 4, 2010
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Conference Paper
Author:
Mykel J. Kochenderfer
…
Published in:
29th Digital Avionics System Conf., 3-7 October 2010.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem that can be solved offline by computers. Prior work has explored methods of efficiently computing the optimal collision avoidance logic from a probabilistic model of aircraft behavior and a cost function. One potential concern with using a probabilistic model to construct the logic is that the model may not adequately represent the real world. Inaccuracies in the model could lead to vulnerabilities in the system when deployed. This paper evaluates the robustness of collision avoidance optimization to modeling errors.
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Summary

Collision avoidance systems, whether for manned or unmanned aircraft, must reliably prevent collision while minimizing alerts. Deciding what action to execute at a particular instant may be framed as a multiple-objective optimization problem that can be solved offline by computers. Prior work has explored methods of efficiently computing the optimal...

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Robustness of optimized collision avoidance logic to modeling errors

A decision-theoretic approach to developing robust collision avoidance logic

September 19, 2010
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Conference Paper
Author:
Mykel J. Kochenderfer
…
Published in:
2010 13th Int. IEEE Annual Conf. on Intelligent Transportation Systems, 19-22 September 2010, pp. 1837-1842.
Topic:
collision avoidance
R&D area:
R&D group:

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. The uncertainty in the behavior of the intruding aircraft makes developing a robust collision avoidance logic challenging. This paper presents an automated approach for optimizing collision avoidance logic based on probabilistic models of aircraft behavior and a performance metric that balances the competing objectives of maximizing safety and minimizing alert rate. The approach involves framing the problem of collision avoidance as a Markov decision process that is solved using dynamic programming. Although this paper focuses on airborne collision avoidance for manned aircraft, the methods may be applied to collision avoidance for other categories of vehicles, both manned and unmanned.
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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. The uncertainty in the behavior of the intruding aircraft makes developing a robust collision avoidance logic challenging. This paper presents an automated approach for...

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A decision-theoretic approach to developing robust collision avoidance logic

Improved Monte Carlo sampling for conflict probability estimation

April 12, 2010
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Conference Paper
Author:
James P. Chryssanthacopoulos
…
Published in:
51st AIAA/ASME/AHS/ACS Structures, Structural Dynamics, and Materials Conf., 12-15 April 2010.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Probabilistic alerting systems for airborne collision avoidance often depend upon accurate estimates of the probability of conflict. Analytical, numerical approximation, and Monte Carlo methods have been applied to conflict probability estimation. The advantage of a Monte Carlo approach is the greater flexibility afforded in modeling the stochastic behavior of aircraft encounters, but typically many samples are required to provide an adequate conflict probability estimate. One approach to improve accuracy with fewer samples is to use importance sampling, where trajectories are sampled according to a proposal distribution that is different from the one specified by the model. This paper suggests several different sample proposal distributions and demonstrates how they result in significantly improved estimates.
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Summary

Probabilistic alerting systems for airborne collision avoidance often depend upon accurate estimates of the probability of conflict. Analytical, numerical approximation, and Monte Carlo methods have been applied to conflict probability estimation. The advantage of a Monte Carlo approach is the greater flexibility afforded in modeling the stochastic behavior of aircraft...

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Improved Monte Carlo sampling for conflict probability estimation

Model-based optimization of airborne collision avoidance logic

January 26, 2010
  |
Project Report
Author:
Mykel J. Kochenderfer
…
Published in:
MIT Lincoln Laboratory Report ATC-360
Topic:
collision avoidance
R&D area:
R&D group:

Summary

The Traffic Alert and Collision Avoidance System (TCAS) is designed to reduce the risk of mid-air collisions by providing resolution advisories to pilots. The current version of the collision avoidance logic was hand-crafted over the course of many years and contains many parameters that have been tuned to varying extents and heuristic rules whose justification has been lost. Further development of the TCAS system is required to make the system compatible with next generation air traffic control procedures and surveillance systems that will reduce separation between aircraft. This report presents a decision-theoretic approach to optimizing the TCAS logic using probabilistic models of aircraft behavior and a cost metric that balances the cost of alerting with the cost of collision. Such an approach ahs the potential for meeting or exceeding the current safety level while lowering the false alert rate and simplifing the process of re-optimizing the logic in response to changes in the airspace and sensor capabilities.
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Summary

The Traffic Alert and Collision Avoidance System (TCAS) is designed to reduce the risk of mid-air collisions by providing resolution advisories to pilots. The current version of the collision avoidance logic was hand-crafted over the course of many years and contains many parameters that have been tuned to varying extents...

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Model-based optimization of airborne collision avoidance logic
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