Contingency Management Concept Generation for U-Space System

Altun, Arinc Tutku; Xu, Yan; Inalhan, Gokhan

doi:10.1109/icns54818.2022.9771531

Cited by 10 publications

(10 citation statements)

References 22 publications

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“…One of the most important tasks of the system will be the contingency management. As detailed in [7], its consideration ramifies throughout the entire system and affects all stakeholders. Safety being the main principle to guide the operations, it will affect other features like flight optimization, preferences or priorities.…”

Section: Related Workmentioning

confidence: 99%

Implementing and Testing a U-Space System: Lessons Learnt

Fas-Millán,

Pick,

Río

et al. 2024

Aerospace

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Within the framework of the European Union’s Horizon 2020 research and innovation program, one of the main goals of the Labyrinth project was to develop and test the Conflict Management services of a U-space-based Unmanned Traffic Management (UTM) system. The U-space concept of operations (ConOps) provides a high-level description of the architecture, requirements and functionalities of these systems, but the implementer has a certain degree of freedom in aspects like the techniques used or some policies and procedures. The current document describes some of those implementation decisions. The prototype included part of the services defined by the ConOps, namely e-identification, Tracking, Geo-awareness, Drone Aeronautical Information Management, Geo-fence Provision, Operation Plan Preparation/Optimization, Operation Plan Processing, Strategic Conflict Resolution, Tactical Conflict Resolution, Emergency Management, Monitoring, Traffic Information and Legal Recording. Moreover, a Web app interface was developed for the operator/pilot. The system was tested in simulations and real visual line of sight (VLOS) and beyond VLOS (BVLOS) flights, with both vertical take-off and landing (VTOL) and fixed-wing platforms, while assisting final users interested in incorporating drones to support their tasks. The development and testing of the environment provided lessons at different levels: functionalities, compatibility, procedures, information, usability, ground control station (GCS) integration and aircrew roles.

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Section: Related Workmentioning

confidence: 99%

Implementing and Testing a U-Space System: Lessons Learnt

Fas-Millán,

Pick,

Río

et al. 2024

Aerospace

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“…Contingency planning and management is an essential objective of drone operations [22]. Altun et al classified contingency hazards in unmanned aircraft systems into five categories: technical failures, human-related failures, datarelated issues, infrastructure-based failures, and environmental events [11]. Technical failures primarily affect drone operation and cause malfunctions such as loss-of-link, GPS failure, navigation degradation, camera failures, and engine and power failures.…”

Section: Introductionmentioning

confidence: 99%

“…Infrastructure-based failures often affect vertiports and lead to availability issues, surface contamination, or debris that may interfere with take-off or landing. Environmental events, such as adverse weather conditions, volcano eruptions, air pollution, and bird strikes, can cause contingency situations [11].…”

Section: Introductionmentioning

confidence: 99%

Contingency Clarification Protocols for Reliable Counter-Drone Operation

Shoufan,

Damiani

2023

IEEE Trans. Aerosp. Electron. Syst.

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Counter-drone technology plays a vital role in protecting airspace against unwanted and malicious drones. Counterdrone systems increasingly rely on unmanned traffic management services, such as remote identification and flight authorization enforcement, for the detection and mitigation of unauthorized activities on the part of Unmanned Aerial Vehicles (UAV). These services support automated drone identification and verification of the drone activity's compliance before taking any enforcement action. Available drone identification standards like ASTM F3411-22 for Drone Remote Identification (DRI) specify key requirements for entities involved in UAV operations. However, DRI systems can fail for many technical and non-technical reasons related to the drone itself, its operator, the identification system, other involved service suppliers, or the communication between these actors. On the other hand, experience has shown that even licensed drone operators can violate permitted flight parameters mistakenly or for unavoidable reasons. In such contingency situations, the counter-drone system should perform additional checks and interact with relevant agents before classifying the drone as illegal and taking action against it. This paper presents a set of protocols to formalize the interaction between the counter-drone system and relevant agents to clarify possible failures and violations. The goal is to complement current DRI systems mitigating the effect of erroneous drone identification and supporting reliable decision-making. The simulation of worst-case scenarios shows that executing the clarification protocols takes just a few seconds, and this delay is only notable in situations where immediate action is required to neutralize illegal drones.

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“…The considered approaches are mainly from vehicle perspective where it is very useful for resolving contingency cases in a low complexity traffic, yet might not work well in a complex traffic environment which is strongly expected to be the case for AAM system. Therefore, the AAM system requires a system-wide contingency management concept which is defined with base requirements in our previous work [9].…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Risk Assessment and Utilization for Contingency Management of Future AAM System

Altun

Tsourdos

et al. 2023

AIAA AVIATION 2023 Forum

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This paper presents a risk assessment methodology to be used in the future Advanced Air Mobility (AAM) systems especially for supporting the planning phase and onboard contingency management solutions. Two types of dynamic risk maps are introduced as Contingency Risk Map that includes the probability of observing a contingency onboard and Risk Severity Map which covers various sources of data such as population density, a dense air traffic, obstacles, terrain, no-fly zones, and so forth. Contingency Risk Map is to quantify the probability of having a contingency and decide if the quantified probability is above the threshold. If the contingency risk probability is at unacceptable limit, Risk Severity Map assists to select a pre-defined secure emergency landing zone or non-secure emergency landing zone defined onboard. The developed risk assessment structure is tested through two different use cases. First one is about defining locations as vertiport alternatives based on the generated map, in case of a contingency ending up with an AAM vehicle to do emergency landing. Second case considers minimum risk onboard rerouting of an AAM vehicle to a secure/non-secure emergency landing zone under contingency management process. The main objective of this work is to build a system-wide contingency management concept for the AAM system by supporting with UTM services such as risk analysis assistance.

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Contingency Management Concept Generation for U-Space System

Cited by 10 publications

References 22 publications

Implementing and Testing a U-Space System: Lessons Learnt

Implementing and Testing a U-Space System: Lessons Learnt

Contingency Clarification Protocols for Reliable Counter-Drone Operation

Comprehensive Risk Assessment and Utilization for Contingency Management of Future AAM System

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