Three-dimensional (3D) Monte-Carlo modeling for UAS collision risk management in restricted airport airspace

Wang, C.; Tan, Shi Kun; Low, Kin Huat

doi:10.1016/j.ast.2020.105964

Cited by 34 publications

(22 citation statements)

References 30 publications

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“…On the other hand, the observed longitudinal distribution did not consistently follow a normal distribution, which coupled with the wide motion range of the multi-rotor vehicle would greatly affect the positional distribution of the leading vehicle (as shown in Ref. [34]) and the buffer distance needed. The longitudinal distribution could further deviate from normal if the mission involves multiple acceleration/deceleration phases.…”

Section: Comparison With Simulation Modelmentioning

confidence: 94%

“…More recently, this 3D Gas Model was adapted for the estimation of UAS collision in the BUBBLE project under SESAR [14]. The Reich collision risk model concept was also adapted, with the addition of kinematic limited randomized agent movements, for UAS collision risk studies under ATMRI [33], [34]. Ultimately, whether the probability distribution funciton for the traffic distribution in question is derived by data-driven distribution or randomized motion based distribution, the collection and evaluation or TSE for aircraft position distribution is essential to support the establishment of separation requirements be it at the strategic (route-design) or tactical (separation minima) level.…”

Section: A Determination Of Separation Requirementsmentioning

confidence: 99%

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Investigation and Modeling of Flight Technical Error (FTE) Associated With UAS Operating With and Without Pilot Guidance

Wang

Low

2021

IEEE Trans. Veh. Technol.

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With the increasing interest in the utilization of urban airspace for unmanned aerial system (UAS) operations, be it for cargo delivery or passenger transportation, the future city sky could become quite a crowded place if all those visions become reality. In such case, the question of how close two operations could be conducted while sharing an airspace must be answered to ensure the safe and efficient use of the urban airspace. The lateral separation needed to prevent inadvertent intrusion by neighboring tracks is especially important when designing airspace corridors constrained by the urban landscape. This paper documents a series of flight tests conducted in open fields with the goal of assessing the along-track (longitudinal), cross-track (lateral),and altitude (height) deviation under two different flight conditions: operator guided operation within Visual Line of Sight (VLoS), and the waypoint-guided mission analogous to operating Beyond Visual Line of Sight (BVLoS). The flight test statistics were also compared to the Monte-Carlo based path prediction model that was used in earlier studies for collision prediction. The goal is to determine the Flight Technical Error (FTE) that forms a part of the Total System Error (TSE) for Performance Based Navigation (PBN) of UAS to support the establishment of separation requirements in urban airspace.

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Section: Comparison With Simulation Modelmentioning

confidence: 94%

Section: A Determination Of Separation Requirementsmentioning

confidence: 99%

Investigation and Modeling of Flight Technical Error (FTE) Associated With UAS Operating With and Without Pilot Guidance

Wang

Low

2021

IEEE Trans. Veh. Technol.

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“…What is more, the third-party risk [41] (i.e. ground people, manned aircraft) can also be mitigated because the high LoA is assumed to have abilities to avoid high risk areas by conducting risk-based path planning [42], [43], and by performing conflict resolutions with manned and other unmanned aircraft with advanced DAA capabilities [44]. UAS with higher LoA would also help improve the efficiency of the UTM network.…”

Section: A Overview Of Loamentioning

confidence: 99%

Framework of Level-of-Autonomy-based Concept of Operations: UAS Capabilities

Pang

Wang

Low

2021

2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC)

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The utility of unmanned aircraft system (UAS) is growing fast in recent years with applications like parcel delivery and security patrol. However, most of the current applications require the involvement of human operator, posing challenges for large-scale UAS deployment due to the operator's and air traffic control officer's (ATCO) limited cognitive capability to control and monitor the traffic. Autonomous UAS operation that reduces the operator and ATCO workload could be a promising solution to meet that challenge. The main aim of this paper, therefore, is to propose a conceptual framework for Level of Autonomy (LoA) based concept of operations (ConOps). The discussion includes the definition and evaluation of LoA and the investigation opportunities of enabling UAS operation at various LoA via case studies. This could be further extended for mixed operation with vehicles of multiple LoA. The framework is presented around core factors defining levels of autonomy for UAS and character for each level in terms of operational actions. Two use cases involving scheduled parcel delivery and non-scheduled emergency operation are presented to demonstrate the evaluation of LoA for a given operation. The proposed framework could serve to identify opportunities for research and engineering development of UAS operations in urban environments.

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“…In addition, drones are constantly enriching people's lives and leading to the modification of industry models. Though drone designers have introduced the high robust flight control system [2,3], intelligent cooperative scheme [4,5], collision avoidance algorithms [6,7] and collision avoidance systems [8,9] to drones, collision safety issues are inevitable for the restrictions on the reliability of the drone itself and the professionalism of the operators.…”

Section: Introductionmentioning

confidence: 99%

A Simplified FE Modeling Strategy for the Drop Process Simulation Analysis of Light and Small Drone

Zhang

Huang

et al. 2021

Aerospace

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The numerical accuracy of drop process simulation and collision response for drones is primarily determined by the finite element modeling method and simplified method of drone airframe structure. For light and small drones exhibiting diverse shapes and configurations, mixed materials and structures, deformation and complex destruction behaviors, the way of developing a reasonable and easily achieved high-precision simplified modeling method by ensuring the calculation accuracy and saving the calculation cost has aroused increasing concern in impact dynamics simulation. In the present study, the full-size modeling and simplified modeling methods that are specific to different components of a relatively popular light and small drone were analyzed in an LS-DYNA software environment. First, a full-size high-precision model of the drone was built, and the model accuracy was verified by performing the drop tests at the component level as well as the whole machine level. Subsequently, based on the full-size high-precision model, the property characteristics of the main components of the light and small drone and their common simplification methods were classified, a series of simplified modeling methods for different components were developed, several single simplified models and combined simplified models were built, and a method to assess the calculation error of the peak impact load in the simplified models was proposed. Lastly, by comparing and analyzing the calculation accuracy of various simplified models, the high-precision simplified modeling strategy was formulated, and the suggestions were proposed for the impact dynamics simulation of the light and small drone falling. Given the analysis of the calculation scale and solution time of the simplified model, the high-precision simplified modeling method developed here is capable of noticeably reducing the modeling difficulty, the solution scale and the calculation time while ensuring the calculation accuracy. Moreover, it shows promising applications in several fields (e.g., structure design, strength analysis and impact process simulation of drone).

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Three-dimensional (3D) Monte-Carlo modeling for UAS collision risk management in restricted airport airspace

Cited by 34 publications

References 30 publications

Investigation and Modeling of Flight Technical Error (FTE) Associated With UAS Operating With and Without Pilot Guidance

Investigation and Modeling of Flight Technical Error (FTE) Associated With UAS Operating With and Without Pilot Guidance

Framework of Level-of-Autonomy-based Concept of Operations: UAS Capabilities

A Simplified FE Modeling Strategy for the Drop Process Simulation Analysis of Light and Small Drone

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