Publications

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...

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...

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...

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, 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...

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 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 recent development of high-fidelity U.S. airspace encounter models at Lincoln Laboratory has motivated a simulation study of the Traffic Alert and Collision Avoidance System (TCAS) multiple threat logic. We observed from archived radar data that while rarer than single-threat encounters, multiple threat encounters occur more frequently than originally expected...

This report documents the Lincoln Laboratory evaluation of the Traffic Alert and Collision Avoidance System II (TCAS II) logic version 7.1. TCAS II is an airborne collision avoidance system required since 30 December 1993 by the FAA on all air carrier aircraft with more than 30 passenger seats operating in...

Appendix to Project Report ATC-346, Evaluation of TCAS II Version 7.1 Using the Fast-Time Encounter Generator Model, Volume 1.