Mid-Air Collision Risk And Areas Of High Benefit For Traffic Alerting by Kunzi, Fabrice, Hansman, Robert J., Jr.

“…As a first step in the development of this application, an analysis of ten years of NTSB mid-air collision reports was conducted to identify areas of high mid-air collision risk. …”
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Toward Mid-Air Collision-Free Trajectory for Autonomous and Pilot-Controlled Unmanned Aerial Vehicles by Kaya Kuru, John Michael Pinder, Benjamin Jon Watkinson, Darren Ansell, Keith Vinning, Lee Moore, Chris Gilbert, Aadithya Sujit, David Jones

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Application of Bayesian Networks and Information Theory to Estimate the Occurrence of Mid-Air Collisions Based on Accident Precursors by Rosa María Arnaldo Valdés, Schon Z.Y. Liang Cheng, Victor Fernando Gómez Comendador, Francisco Javier Sáez Nieto

“…This paper combines Bayesian networks (BN) and information theory to model the likelihood of severe loss of separation (LOS) near accidents, which are considered mid-air collision (MAC) precursors. BN is used to analyze LOS contributing factors and the multi-dependent relationship of causal factors, while Information Theory is used to identify the LOS precursors that provide the most information. …”
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Preliminary Feasibility Study of the Ad Hoc Separation Operational Concept by Lidia Serrano-Mira, Luis Pérez Sanz, Javier A. Pérez-Castán, Fedja Netjasov, Irene García Moreno, Eduardo S. Ayra

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Vision-Based Mid-Air Object Detection and Avoidance Approach for Small Unmanned Aerial Vehicles with Deep Learning and Risk Assessment by Ying-Chih Lai, Tzu-Yun Lin

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What Matters in the Effectiveness of Airborne Collision Avoidance Systems? Monte Carlo Simulation of Uncertainties for TCAS II and ACAS Xa by Sybert Stroeve

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Mid-air hand interaction with optical tracking for 3D modelling by Cui, Jian

“…After surveying the relevant works and analyzing technical capabilities of the commonly available optical sensors, two approaches are thoroughly investigated for the natural mid-air hand interaction in precise 3D modeling – they are collision-based and gesture-based interaction. …”
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Human Factors Studies of an ADS-B Based Traffic Alerting System for General Aviation by Silva, Sathya, Cho, HongSeok, Gao, Hang, Kunzi, Fabrice, Hansman, R. John

Subjects: “…mid-air collisions…”
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A STAMP model of the Überlingen aircraft collision accident by Wong, Brian, 1982 Nov 11-

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Airspace capacity overload identification using collision risk patterns by Ma, Chunyao, Cai, Qing, Alam, Sameer, Duong, Vu N.

“…Since the primary task of air traffic controllers is to manage traffic flow within the constraints imposed by safety requirements, i.e., to warrant the collision risk at a low level, in this paper, we use the aircraft mid-air collision risk for a given airspace as the indicator of airspace capacity overload. …”
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Parametric Study of Structured UTM Separation Recommendations with Physics-Based Monte Carlo Distribution for Collision Risk Model by Chung-Hung John Wang, Chao Deng, Kin Huat Low

“…One layer of defense against mid-air-collision and the ensuing third-party injury or fatality is the pre-flight separation assurance. …”
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Pre-tactical airspace collision risk model for air traffic controller by Ngoi, Kai Ling

“…This will potentially lead to mid-air collision. With the increasing workload, more errors will be made by ATCOs that contributes to mid-air collision. …”
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Multi-objective optimization of next-generation aircraft collision avoidance software by Lepird, John R

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Quantifying Specific Operation Airborne Collision Risk through Monte Carlo Simulation by Aliaksei Pilko, Mario Ferraro, James Scanlan

“…Integration of Uncrewed Aircraft into unsegregated airspace requires robust and objective risk assessment in order to prevent exposure of existing airspace users to additional risk. A probabilistic Mid-Air Collision risk model is developed based on surveillance traffic data for the intended operational area. …”
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Investigating Collision Avoidance for Small UAS using Cooperative Surveillance and ACAS X by Deaton, John L., Hansman, R. John

“…While these platforms offer many benefits to society, they pose a dangerous mid-air collision hazard. In order to safely integrate into airspace shared by other users, sUAS must be able to avoid collisions with manned aircraft. …”
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Investigating collision avoidance for small UAS using cooperative surveillance and ACAS X by Deaton, John Logan.

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Aircraft collision avoidance using Monte Carlo Real-Time Belief Space Search by Wolf, Travis Benjamin

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Collision avoidance system optimization for closely spaced parallel operations through surrogate modeling by Smith, Kyle A. (Kyle Alexander)

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Vision-Based In-Flight Collision Avoidance Control Based on Background Subtraction Using Embedded System by Jeonghwan Park, Andrew Jaeyong Choi

“…One of the key features of an autonomous UAV is a robust mid-air collision avoidance strategy. This paper proposes a vision-based in-flight collision avoidance system based on background subtraction using an embedded computing system for unmanned aerial vehicles (UAVs). …”
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Same-track UAS separation requirement evaluation with Monte-Carlo based collision risk modeling by Wang, John Chung Hung, Deng, Chao, Low, Kin Huat

“…To determine the separation needed to prevent mid-air collision for UAS, specifically multirotor, traveling along the same track, a modified Reich collision risk model with multirotor specific flight dynamics and Monte-Carlo method was used. …”
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