Publications
MIT Lincoln Laboratory TCAS surveillance performance
Summary
Summary
The Traffic Alert and Collision Avoidance System (TCAS) Version 7 surveillance requirements were developed in the mid-1990s with the use of limited radar data. Recently, a more comprehensive radar data source has become available, enabling a thorough analysis of TCAS surveillance performance throughouth the National Airspace System (NAS). This paper...
Robustness of optimized collision avoidance logic to modeling errors
Summary
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...
A decision-theoretic approach to developing robust collision avoidance logic
Summary
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...
Benefits assessment methodology for an air traffic control tower advanced automation system
Summary
Summary
This paper presents a benefits assessment methodology for an air traffic control tower advanced automation system called the Tower Flight Data Manager (TFDM), which is being considered for development by the FAA to support NextGen operations. The standard FAA benefits analysis methodology is described, together with how it has been...
On estimating mid-air collision risk
Summary
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...
Collision avoidance for unmanned aircraft using Markov Decision Processes
Summary
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...
Improved Monte Carlo sampling for conflict probability estimation
Summary
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...
Airspace encounter models for estimating collision risk
Summary
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...
Model-based optimization of airborne collision avoidance logic
Summary
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...
Classification of primary radar tracks using Gaussian mixture models
Summary
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...