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Aerospace
Special Issues
Recent Advances in See and Avoid Systems for Aircraft
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Recent Advances in See and Avoid Systems for Aircraft

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: closed (31 July 2022) | Viewed by 8594

Special Issue Editor

Dr. Federico Corraro

E-Mail Website
Guest Editor
Department of Innovative Systems and Applications of Satellite Navigation, Centro Italiano Ricerche Aerospaziali, 81043 Capua, Italy
Interests: GNSS technologies and applications; detect/see and avoid systems; autonomous guidance and trajectory planning; multisensor navigation; flight control systems; modeling and analysis of dynamical uncertain systems; post-flight analysis and model identification

Special Issue Information

Dear Colleagues,

So far, due to aviation authorities′ constraints for flight safety, remotely piloted aircraft systems (RPASs) can only fly in segregated areas, making their integration in the civil airspace a great challenge. Moreover, smaller unmanned aerial vehicles (UAVs) are going to be massively used at low altitudes (typically below 500 ft) for several applications (security, environmental monitoring, disaster support, etc.). In this scenario, see and avoid (SAA) or detect and avoid (DAA) technology has been identified as a key enabling factor for the full integration of RPASs and UAVs into the civil, not-segregated, airspace to be shared with already existing manned aircraft.

However, despite the above need and the huge research effort on this topic lasting more than 15 years, the proposed solutions can be applicable only to some specific unmanned vehicles under limited operating conditions, usually not including fully autonomous flights. These solutions can be acceptable in the short term but are not suitable to cope with the increase in RPAS and UAV traffic and autonomy that is predicted in the mid and long term. 

The key improvement areas that the most recent advances in SAA technology should be focused on are related (but not limited) to:

  • Technologies for accurately sensing traffic and fixed obstacles that can be integrated in all vehicle’s classes (from a few kilograms to several tons);
  • Efficient filters for processing and fusing sensor data to reliably see and detect obstacles (either flying or not-flying);
  • Intelligent traffic conflict detection, situational awareness, and guidance algorithms to allow missions near ground, in urban areas, or in the presence of other path constraints (fixed obstacles, severe weather, no-fly zones, geo-fencing) that would enable more autonomous unmanned operations;
  • Better adaptation of SAA to (variable) vehicle maneuvering capabilities and to the probabilistic nature of traffic evolution, to always have an optimized behavior in any situation.

Dr. Federico Corraro
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Research

33 pages, 5567 KiB  
Article
Implementation and Real-Time Validation of a European Remain Well Clear Function for Unmanned Vehicles
by Gianluca Corraro, Federico Corraro, Umberto Ciniglio, Edoardo Filippone, Niklas Peinecke and Erik Theunissen
Aerospace 2022, 9(10), 531; https://0-doi-org.brum.beds.ac.uk/10.3390/aerospace9100531 - 21 Sep 2022
Cited by 4 | Viewed by 1674
Abstract
The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from [...] Read more.
The full integration of Remotely Piloted unmanned vehicles into civil airspace requires first and foremost the integration of a traffic Detect and Avoid (DAA) system into the vehicle. The DAA system supports remote pilots in performing their task of remaining Well Clear from other aircraft and avoiding collisions. Several studies related to the design of a Remain Well Clear function have been performed that served as input for the development of technical standards applicable to non-European countries. In this paper, a Remain Well Clear implementation is proposed that, using the results of past international projects, fits European airspace needs and specificities and can be acceptable to both remote pilots and air traffic controllers, with only minimal impact on the standard operating procedures used for manned aircraft. The proposed Remain Well Clear software has been successfully validated through real-time simulations with pilots and controllers in the loop considering traffic encounters and mission scenarios typically found in European airspace. The achieved results highlight the appropriate situational awareness provided by the proposed RWC function and its effective support to the remote pilot in making adequate decisions in conflict solving. Real-time simulation tests showed that, in almost all cases, an RWC maneuver is successfully performed, giving the RP sufficient time to assess the conflict, coordinate with the controller, if needed, and execute the maneuver. The fundamental role of the proposed RWC function has been especially evident in uncontrolled airspace classes where the controller does not provide any separation provision. Moreover, its effectiveness has also been tested in encounters with aircraft flying under visual flight rules in controlled airspace, where the controller is not informed or has less information regarding these aircraft. The results from validation tests imply two key potential safety benefits, namely: the mitigation of performing a collision avoidance maneuver and the prevention of potential conflict while not disrupting the traffic flow with possible further consequences of generating other potentially hazardous situations. Full article
(This article belongs to the Special Issue Recent Advances in See and Avoid Systems for Aircraft)
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28 pages, 6599 KiB  
Article
Unmanned Aircraft Collision Detection and Avoidance for Dealing with Multiple Hazards
by Federico Corraro, Gianluca Corraro, Giovanni Cuciniello and Luca Garbarino
Aerospace 2022, 9(4), 190; https://0-doi-org.brum.beds.ac.uk/10.3390/aerospace9040190 - 01 Apr 2022
Cited by 3 | Viewed by 2583
Abstract
Collision Detection and Avoidance is one of the critical technologies for fully allowing Unmanned Aerial Systems to fly in civil airspaces. Current methods evaluate only potential conflicts with other aircraft using specific parameters (e.g., time or distance to closest point of approach) that [...] Read more.
Collision Detection and Avoidance is one of the critical technologies for fully allowing Unmanned Aerial Systems to fly in civil airspaces. Current methods evaluate only potential conflicts with other aircraft using specific parameters (e.g., time or distance to closest point of approach) that can only be used for pair-wise encounters, not considering the surrounding environment. The present work proposes a new Collision Detection and Avoidance concept to solve short-term conflicts in scenarios characterized by the simultaneous presence of aircraft and other path constraints (i.e., no-fly zones, bad weather areas and terrain) including geo-fencing limitations. Differently from other open literature methods, the proposed algorithm computes two parameters that synthetically describe the conflict hazard level of a given scenario and its possible evolution, independently from the type and the number of surrounding potential threats. Using such indices, a risk evaluation strategy is proposed that detects hazardous situations and generates an optimal maneuver avoiding potential collisions while not causing secondary conflicts. The effectiveness of the proposed algorithm is demonstrated by means of fast-time and real time simulations in some challenging conflict scenarios that cannot be solved by state of the art Detect and Avoid systems. Full article
(This article belongs to the Special Issue Recent Advances in See and Avoid Systems for Aircraft)
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19 pages, 4736 KiB  
Article
Probabilistic Risk Analysis of Aircraft Self-Collisions: A Case Study
by Dooyoul Lee, Hwanjeong Cho, Min-Saeng Kim and Kybeom Kwon
Aerospace 2022, 9(2), 80; https://0-doi-org.brum.beds.ac.uk/10.3390/aerospace9020080 - 01 Feb 2022
Viewed by 1528
Abstract
Airborne self-collisions occur primarily in military aircraft because of external stores and are frequently experienced by personnel operating these aircraft. In most cases, objects causing self-collisions are irregularly shaped and unstable. Consequently, the trajectories of these objects are uncertain. A framework for the [...] Read more.
Airborne self-collisions occur primarily in military aircraft because of external stores and are frequently experienced by personnel operating these aircraft. In most cases, objects causing self-collisions are irregularly shaped and unstable. Consequently, the trajectories of these objects are uncertain. A framework for the probabilistic risk analysis of aircraft self-collisions is proposed in this study. Based on the probabilistic trajectory prediction model, methods for estimating the probability of collision (POC) and the corresponding risks were developed. Subsequently, a self-collision event involving an ejected gun shell was analyzed as a case study. A model considering random shell rotation, which continuously changes the drag characteristics and trajectories, was developed. Other uncertain factors associated with the aircraft and shell cases were considered. The most influential factors were selected based on the sensitivity analysis and were then used to calibrate the likelihood of the event using historical data. A Monte Carlo simulation, in conjunction with the probabilistic ballistic model, was performed to evaluate the POC. The POC was used to reflect the risk of engine failure up to the operational limit. The calculated risk indices were objective functions used for the design or operation optimization. Various risk measures were evaluated to reduce the incidence of failure and extend the aircraft’s flight envelope. Full article
(This article belongs to the Special Issue Recent Advances in See and Avoid Systems for Aircraft)
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