Publications
Tagged As
Unmanned aircraft collision avoidance using partially observable 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, this project investigates the automatic generation of collision avoidance logic given models of aircraft dynamics, sensor performance, and...
Safety analysis of upgrading to TCAS Version 7.1 using the 2008 U.S. Correlated Encounter Model
Summary
Summary
As a result of monitoring and modeling efforts by Eurocontrol and the FAA, two change proposals have been created to change the TCAS II V9.0 logic. The first, CP-112E, addresses the safety issues referred to as SA01. SA01 events have to do with the reversal logic contained in the TCAS...
Evaluation of TCAS II Version 7.1 using the FAA Fast-Time Encounter Generator model [volume 1]
Summary
Summary
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...
Evaluation of TCAS II Version 7.1 using the FAA Fast-Time Encounter Generator model : appendix [volume 2]
Summary
Summary
Appendix to Project Report ATC-346, Evaluation of TCAS II Version 7.1 Using the Fast-Time Encounter Generator Model, Volume 1.
Encounter models for unconventional aircraft version 1.0
Summary
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...
Airspace encounter models for conventional and unconventional aircraft
Summary
Summary
Collision avoidance systems play an important role in the future of aviation safety. Before new technologies on board manned or unmanned aircraft are deployed, rigorous analysis using encounter simulations is required to prove system robustness. These simulations rely on models that accurately reflect the geometries and dynamics of aircraft encounters...
A comprehensive aircraft encounter model of the National Airspace System
Summary
Summary
Collision avoidance systems play an important role in the future of aviation safety. Before new technologies on board manned or unmanned aircraft are deployed, rigorous analysis using encounter simulations is required to prove system robustness. These simulations rely on models that accurately reflect the geometries and dynamics of aircraft encounters...
Uncorrelated encounter model of the National Airspace System version 1.0
Summary
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...
Correlated encounter model for cooperative aircraft in the National Airspace System, version 1.0
Summary
Summary
This document describes a new cooperative aircraft encounter model for the National Airspace System (NAS). The model is used to generate random close encounters between transponder-equipped (cooperative) aircraft in fast-time Monte Carlo simulations to evaluate collision avoidance system concepts. An extensive set of radar data from across the United States...
A Bayesian approach to aircraft encounter modeling
Summary
Summary
Aircraft encounter models can be used in a variety of analyses, including collision avoidance system safety assessment, sensor design trade studies, and visual acquisition analysis. This paper presents an approach to airspace encounter model construction based on Markov models estimated from radar data. We use Bayesian networks to represent the...