Publications

Refine Results

(Filters Applied) Clear All

By

Robustness of optimized collision avoidance logic to modeling errors

October 4, 2010
  |
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.
READ LESS

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...

READ MORE
Robustness of optimized collision avoidance logic to modeling errors

A decision-theoretic approach to developing robust collision avoidance logic

September 19, 2010
  |
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.
READ LESS

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...

READ MORE
A decision-theoretic approach to developing robust collision avoidance logic

On estimating mid-air collision risk

September 13, 2010
  |
Conference Paper
Author:
Mykel J. Kochenderfer
…
Published in:
ATIO 2010: 10th AIAA Aviation Technology Integration and Operations Conf., 13-15 September 2010.
Topic:
air traffic control
R&D area:
R&D group:

Summary

Many aviation safety studies involve estimating near mid-air collision (NMAC) rate. In the past, it has been assumed that the probability that an NMAC leads to a mid-air collision is 0.1, but there has not yet been a comprehensive study to serve as a basis for this estimate. This paper explains how to use existing encounter models, a flight simulation framework, three-dimensional aircraft wireframe models, and surveillance data to estimate mid-air collision risk. The results show that 0.1 is an overly conservative estimate and that the true rate is likely to be an order of magnitude lower.
READ LESS

Summary

Many aviation safety studies involve estimating near mid-air collision (NMAC) rate. In the past, it has been assumed that the probability that an NMAC leads to a mid-air collision is 0.1, but there has not yet been a comprehensive study to serve as a basis for this estimate. This paper...

READ MORE
On estimating mid-air collision risk

Collision avoidance for unmanned aircraft using Markov Decision Processes

August 2, 2010
  |
Conference Paper
Author:
Selim Temizer
…
Published in:
AIAA Guidance, Navigation, and Control Conf., 2-5 August 2010.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Before unmanned aircraft can fly safely in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft configuration, we investigate the automatic generation of collision avoidance algorithms given models of aircraft dynamics, sensor performance, and intruder behavior. By formulating the problem of collision avoidance as a Markov Decision Process (MDP) for sensors that provide precise localization of the intruder aircraft, or a Partially Observable Markov Decision Process (POMDP) for sensors that have positional uncertainty or limited field-of-view constraints, generic MDP/POMDP solvers can be used to generate avoidance strategies that optimize a cost function that balances flight-plan deviation with collision. Experimental results demonstrate the suitability of such an approach using four different sensor modalities and a parametric aircraft performance model.
READ LESS

Summary

Before unmanned aircraft can fly safely in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft configuration, we investigate the automatic generation of collision avoidance algorithms given models of aircraft dynamics, sensor performance, and intruder...

READ MORE
Collision avoidance for unmanned aircraft using Markov Decision Processes

Improved Monte Carlo sampling for conflict probability estimation

April 12, 2010
  |
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.
READ LESS

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...

READ MORE
Improved Monte Carlo sampling for conflict probability estimation

Airspace encounter models for estimating collision risk

March 1, 2010
  |
Journal Article
Author:
Mykel J. Kochenderfer
…
Published in:
J. Guidance, Control, and Dynamics, Vol. 33, No. 2, March-April 2010, pp. 487-499.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Airspace encounter models, providing a statistical representation of geometries and aircraft behavior during a close encounter, are required to estimate the safety and robustness of collision avoidance systems. Prior encounter models, developed to certify the Traffic Alert and Collision Avoidance System, have been limited in their ability to capture important characteristics of encounters as revealed by recorded surveillance data, do not capture the current mix of aircraft types or noncooperative aircraft, and do not represent more recent airspace procedures. This paper describes a methodology for encounter model construction based on a Bayesian statistical framework connected to an extensive set of national radar data. In addition, this paper provides examples of using several such high-fidelity models to evaluate the safety of collision avoidance systems for manned and unmanned aircraft.
READ LESS

Summary

Airspace encounter models, providing a statistical representation of geometries and aircraft behavior during a close encounter, are required to estimate the safety and robustness of collision avoidance systems. Prior encounter models, developed to certify the Traffic Alert and Collision Avoidance System, have been limited in their ability to capture important...

READ MORE
Airspace encounter models for estimating collision risk

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.
READ LESS

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...

READ MORE
Model-based optimization of airborne collision avoidance logic

Classification of primary radar tracks using Gaussian mixture models

December 22, 2009
  |
Journal Article
Author:
Leo P. Espindle
…
Published in:
IET Radar, Sonar Navig., Vol. 3, No. 6, December 2009.
Topic:
radar
R&D area:
R&D group:

Summary

Classification of primary surveillance radar tracks as either aircraft or non-aircraft is critical to a number of emerging applications, including airspace situational awareness and collision avoidance. Substantial research has focused on target classification of pre-processed radar surveillance data. Unfortunately, many non-aircraft tracks still pass through the clutter-reduction processing built into the aviation surveillance radars used by the Federal Aviation Administration. This paper demonstrates an approach to radar track classification that uses only post-processed position reports and does not require features that are typically only available during the pre-processing stage. Gaussian mixture models learned from recorded data are shown to perform well without the use of features that have been traditionally used for target classification, such as radar crosssection measurements.
READ LESS

Summary

Classification of primary surveillance radar tracks as either aircraft or non-aircraft is critical to a number of emerging applications, including airspace situational awareness and collision avoidance. Substantial research has focused on target classification of pre-processed radar surveillance data. Unfortunately, many non-aircraft tracks still pass through the clutter-reduction processing built into...

READ MORE
Classification of primary radar tracks using Gaussian mixture models

Unmanned aircraft collision avoidance using partially observable Markov decision processes

September 22, 2009
  |
Project Report
Author:
Mykel J. Kochenderfer
…
Published in:
MIT Lincoln Laboratory Report ATC-356
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Before unmanned aircraft can fly safely in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft configuration, this project investigates the automatic generation of collision avoidance logic given models of aircraft dynamics, sensor performance, and intruder behavior. By formulating the problem of collision avoidance as a partially-observable Markov decision process (POMDP), a generic POMDP solver can be used to generate avoidance strategies that optimize a cost function that balances flight-plan deviation with collision. Experimental results demonstrate the suitability of such an approach using three different sensor modalities and two aircraft performance models.
READ LESS

Summary

Before unmanned aircraft can fly safely in civil airspace, robust airborne collision avoidance systems must be developed. Instead of hand-crafting a collision avoidance algorithm for every combination of sensor and aircraft configuration, this project investigates the automatic generation of collision avoidance logic given models of aircraft dynamics, sensor performance, and...

READ MORE
Unmanned aircraft collision avoidance using partially observable Markov decision processes

Encounter models for unconventional aircraft version 1.0

April 10, 2009
  |
Project Report
Author:
Matthew W. M. Edwards
…
Published in:
MIT Lincoln Laboratory Report ATC-348
Topic:
collision avoidance
R&D area:
R&D group:

Summary

Airspace encounter models, covering close encounter situations that may occur after standard separation assurance has been lost, are a critical component in the safety assessment of aviation procedures and collision avoidance systems. Of particular relevance to Unmanned Aircraft Systems (UAS) is the potential for encountering general aviation aircraft that are flying under Visual Flight Rules (VFR) and are not in contact with air traffic control. In response to the need to develop a model of these types of encounters, Lincoln Laboratory undertook an extensive data collection and modeling effort involving more than 96,000 unconventional aircraft tracks. The outcome of this effort was nine individual models encompassing ultralights, gliders, balloons, and airships. The models use Bayesian networks to represent relationships between dynamic variables and to construct random trajectories that are statistically similar to those observed in the data. The intruder trajectories can be used in fast-time Monte Carlo simulations to estimate collision risk. The model described in this report is one of three developed by Lincoln Laboratory. A correlated encounter model has been developed to represent situations in which it is likely that there would b e air traffic control intervention prior to a close enounter. The correlated model applies to encounters involving aircraft receiving Air Traffic Control (ATC) services and with transponders. TAn encounter with an intruder that does not have a transponder is uncorrelated in the sense that it is unlikely that there would be prior intervention by air traffic control. The uncorrelated model described in this report is based on global databases of pilot-submitted track data. This work is a follow-on to an uncorrelated conventional model developed from recorded radar tracks from aircraft using a 1200 transponder code. A byproduct of this encounter modeling effort was the extraction of feature distributions for unconventional aircraft. This provides an extensive collection of unconventional aircraft behavior in the airspace.
READ LESS

Summary

Airspace encounter models, covering close encounter situations that may occur after standard separation assurance has been lost, are a critical component in the safety assessment of aviation procedures and collision avoidance systems. Of particular relevance to Unmanned Aircraft Systems (UAS) is the potential for encountering general aviation aircraft that are...

READ MORE
Encounter models for unconventional aircraft version 1.0
21-30 of 38