CERES :: Browsing by Author "Xu, Yan"

Browsing by Author "Xu, Yan"

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Open Access
4D trajectory optimization of commercial flight for green civil aviation
(IEEE, 2020-03-31) Tian, Yong; He, Xiuqi; Xu, Yan; Wan, Lili; Ye, Bojia
For the current development of green civil aviation, this study aims to optimize the green four-dimensional (4D) trajectory of commercial flight by taking into account conventional cost and environmental cost. Some fundamental models, efficient processing methodologies, and conventional objectives are proposed to construct the framework of trajectory optimization. Based on the environmental cost including greenhouse gas cost and harmful gas cost, green objective functions are presented. The A* algorithm and the trapezoidal collocation method are employed to optimize the lateral path and vertical profile for 4D optimization trajectory generation. A case study for the A320 from Barcelona Airport to Frankfurt Airport yields the results that the optimal costs can be obtained under different objectives and the total cost can be more optimized by adjusting the weights of environmental cost and conventional cost. The study builds an aided tool for 4D trajectory optimization and demonstrates that environmental factors and conventional factors should be taken into comprehensive consideration when constructing the flight trajectory in the future, as well as it can underpin the green and sustainable development of the air transport industry.
Open Access
A 4D-trajectory planning method based on hybrid optimization strategy for demand and capacity balancing
(IEEE, 2021-11-15) Chen, Yutong; Xu, Yan; Hu, Minghua; Huang, Fei; Nie, Qi
To effectively solve the Demand and Capacity Balancing (DCB) in future Trajectory-Based Operation (TBO) scenarios, this article first proposes a pre-tactical-and-tactical integrated Four-Dimensional Trajectory (4DT) planning framework. The framework decomposes large-scale 4DT planning into two stages, namely, the General 4DT (G4DT) planning in the pre-tactical stage and the Special 4DT (S4DT) planning in the tactical stage. A Hybrid Optimization Strategy (HOS) based planning method is designed for G4DT planning. In this method, the sequential decision architecture based on time window, heuristic strategy (greedy strategy) and optimization algorithm are combined to realize the fast trajectory planning of large-scale flights. In the optimization model based on continuous time, the nonlinear model is transformed into a linear model by constructing the flight conflict correlation matrix, which greatly improves the solving speed of the model. Real flight schedule data for French and Spanish airspace were used to verify the effectiveness and efficiency of the HOS method. This method is compared with Computer-Assisted Slot Allocation (CASA). The results show that the proposed method can effectively reduce the flight delay time and improve the flight on-time rate. Due to its fast operation speed, the proposed method has great potential to dynamically update the planning results according to the real-time air space operation status in actual operation.
Open Access
A risk assessment method for mid-air collisions in urban air mobility operations
(Institute of Electrical and Electronics Engineers (IEEE), 2024-12-31) Su, Yu; Xu, Yan
This paper proposes a method to systematically assess the risk of mid-air collisions in Urban Air Mobility (UAM) operations, considering unique flight characteristics, mission requirements, and the evolving airspace dynamics. The method encompasses three pivotal phases: the encounter leading to collision, the loss of control post-collision, and the resulting harm to third parties on the ground or in the air. Instead of focusing solely on the collision risk, this method quantifies potential harms, introducing the metric of “fatalities per flight hour” akin to conventional aviation. Three main barriers, strategic mitigation, tactical mitigation, and collision avoidance, are modelled to calculate the probability of mid-air collisions. The gas model evaluates the probability of strategic mitigation failure, while an encounter timeline concept determines the probability of tactical mitigation failure. This paper concludes with Monte Carlo simulations validating the proposed model and a real-world case study demonstrating its applicability for regulators, operators, and stakeholders in ensuring the safety and efficiency of future UAM operations.
Open Access
AMU-LED Cranfield flight trials for demonstrating the advanced air mobility concept
(MDPI, 2023-08-31) Altun, Arinc Tutku; Hasanzade, Mehmet; Saldiran, Emre; Guner, Guney; Uzun, Mevlut; Fremond, Rodolphe; Tang, Yiwen; Bhundoo, Prithiviraj; Su, Yu; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.; Fransoy, Alejandro; Modha, Ajay; Tena, Jose Antonio; Nieto, Cesar; Vilaplana, Miguel; Tojal, Marta; Gordo, Victor; Menendez, Pablo; Gonzalez, Ana
Advanced Air Mobility (AAM) is a concept that is expected to transform the current air transportation system and provide more flexibility, agility, and accessibility by extending the operations to urban environments. This study focuses on flight test, integration, and analysis considerations for the feasibility of the future AAM concept and showcases the outputs of the Air Mobility Urban-Large Experimental Demonstration (AMU-LED) project demonstrations at Cranfield University. The purpose of the Cranfield demonstrations is to explore the integrated decentralized architecture of the AAM concept with layered airspace structure through various use cases within a co-simulation environment consisting of real and simulated standard-performing vehicle (SPV) and high-performing vehicle (HPV) flights, manned, and general aviation flights. Throughout the real and simulated flights, advanced U-space services are demonstrated and contingency management activities, including emergency operations and landing, are tested within the developed co-simulation environment. Moreover, flight tests are verified and validated through key performance indicator analysis, along with a social acceptance study. Future recommendations on relevant industrial and regulative activities are provided.
Open Access
Analyzing fragility of the advanced air mobility system and exploring antifragile networks
(IEEE, 2023-11-10) Altun, Arinc Tutku; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.
Future Advanced Air Mobility (AAM) is a concept that envisions to transform the current air transportation system into a more agile, flexible, and accessible system. Yet, the considered transformation and integrated system is not easy to achieve since it involves providing a high level of safety as well as efficiency. For that purpose, in this paper, we explored the fragility and antifragility concepts to analyze the AAM traffic network and provide an understanding of a system where it can benefit even under adverse conditions such as contingency events. For the analysis, first, a complex AAM traffic network is built via various AAM vehicles and possible vertiport locations that are analyzed for the Northern California area. After that, the AAM network is modeled via queue theory to simulate the considered flight plans, obtain the actual departure and arrival times under different conditions, and observe the delay propagation. Then, metrics from network theory based on targeted node and edge removals are studied to analyze the fragility of the AAM network and used for antifragility analysis. The methodology is used to analyze different disruptive cases over an AAM network such that disruptions at vertiports and over origin-destination pairs. Finally, an analysis of making the considered traffic antifragile through flight cancellations and its trade-off based on flight cancellation costs is provided.
Open Access
Automatic interval management for aircraft based on dynamic fuzzy speed control considering uncertainty
(Elsevier, 2023-07-13) Yuan, Jie; Pei, Yang; Xu, Yan; Li, Xiaochen; Ge, Yuxue
A novel real-time autonomous Interval Management System (IMS) is proposed to automate interval management, which considers the effect of wind uncertainty using the Dynamic Fuzzy Velocity Decision (DFVD) algorithm. The membership function can be generated dynamically based on the True Air Speed (TAS) limitation changes in real time and the interval criterion of the adjacent aircraft, and combined with human cognition to formulate fuzzy rules for speed adjusting decision-making. Three groups of experiments were conducted during the en-route descent stage to validate the proposed IMS and DFVD performances, and to analyze the impact factors of the algorithm. The verification experimental results show that compared with actual flight status data under controllers’ command, the IMS reduces the descent time by approaching 30% with favorable wind uncertainty suppression performance. Sensitivity analysis shows that the ability improvement of DFVD is mainly affected by the boundary value of the membership function. Additionally, the dynamic generation of the velocity membership function has greater advantages than the static method in terms of safety and stability. Through the analysis of influencing factors, we found that the interval criterion and aircraft category have no significant effect on the capability of IMS. In a higher initial altitude scenario, the initial interval should be appropriately increased to enhance safety and efficiency during the descent process. This prototype system could evolve into a real-time Flight-deck Interval Management (FIM) tool in the future.
Open Access
Co-simulation digital twin framework for testing future advanced air mobility concepts: a study with BlueSky and AirSim
(IEEE, 2023-11-10) Zhao, Junjie; Conrad, Christopher; Fremond, Rodolphe; Mukherjee, Anurag; Delezenne, Quentin; Su, Yu; Xu, Yan; Tsourdos, Antonios
The UK Future Flight Vision and Roadmap outlines the anticipated development of aviation in the UK by 2030. As part of the Future Flight demonstration segment, project HADO (High-intensity Autonomous Drone Operations) will develop, test, and deploy fully automated unmanned aircraft system (UAS) operations at London Heathrow Airport. Cranfield University is leading the synthetic test environment development within the HADO project, and a digital twin (DT) prototype was developed to enable mixed-reality tests for autonomous UAS operations. This paper enhances the existing DT by introducing new co-simulation capacities. Specifically, a co-simulation DT framework for autonomous UAS operations is proposed and tested through a demonstrative use case based on BlueSky and AirSim. This prototype integrates the traffic simulation capabilities of BlueSky with the 3D simulation capabilities of Airsim, to efficiently enhance the simulation capacities of the DT. Notably, the co-simulation framework can leverage the 3D visualization modules, UAS dynamics, and sensor models within external simulation tools to support a more realistic and high-fidelity simulation environment. Overall, the proposed co-simulation method can interface several simulation tools within a DT, thereby incorporating different communication protocols and realistic visualization capabilities. This creates unprecedented opportunities to combine different software applications and leverage the benefits of each tool.
Open Access
A co-simulation digital twin with SUMO and AirSim for testing lane-based UTM system concept
(IEEE, 2024-05-13) Wen, Zhang; Zhao, Junjie; Xu, Yan; Tsourdos, Antonios
The UAS (Unmanned Aircraft System) Traffic Management (UTM) System Concept of Operations (ConOps) is the first formal design reference document of the UTM system, ConOps aims to bring Class G Airspace into government regulation. However, it should be noted that there are still some shortcomings in ConOps that require further discussion. For example, there are concerns about operational rights, privacy rights, and the potential interference caused by high-rise buildings in urban core areas. The Lane-based UTM systems could potentially help in solving the above issues. The flight paths of Unmanned Aerial Vehicles (UAVs) in urban areas or other areas will interact with the road network, which can facilitate airspace traffic development. Ground traffic flow simulation is generally conducted on three levels: macroscopic, mesoscopic, and microscopic. Some of the commonly used car traffic flow simulation tools include Vissim, SUMO, and MATSim. However, UAV traffic simulation is mostly at a single level, and all of the current mainstream simulation software for UAV, such as Gazebo, AirSim, and Flight Gear, are microscopic-level analyses of UAV operations, lacking uniform management of drone traffic flow and operations. In addition, these UAV traffic simulation studies do not consider the city traffic and road network. In this context, a lane-based cosimulation UAV traffic simulation method is proposed in this study. The co-simulation architecture will be based on the highfidelity three-dimensional (3D) environment developed in the Unreal Engine, UAV simulation with AirSim, and twodimensional (2D) road network simulation with SUMO. A standardized and universal co-simulation architecture and communication interface to ensure interoperability, compatibility, and synchronization will be developed in this study. The lane-based co-simulation method will effectively leverage the road network simulation capacities to turn complex 3D space planning into simple 2D planning, it could reduce computational load and improve system efficiency. The 3D environment will also enhance the simulation capacities with its unique and high-fidelity simulation capacities. Overall, the proposed co-simulation method will support the Digital Twin development by interfacing several simulation tools, incorporating different communications, and adding realistic visualization, which could create unprecedented opportunities for software tool combinations.
Open Access
CogEmoNet: A cognitive-feature-augmented driver emotion recognition model for smart cockpit
(IEEE, 2021-11-30) Li, Wenbo; Zeng, Guanzhong; Zhang, Juncheng; Xu, Yan; Xing, Yang; Zhou, Rui; Guo, Gang; Shen, Yu; Cao, Dongpu; Wang, Fei-Yue
Driver's emotion recognition is vital to improving driving safety, comfort, and acceptance of intelligent vehicles. This article presents a cognitive-feature-augmented driver emotion detection method that is based on emotional cognitive process theory and deep networks. Different from the traditional methods, both the driver's facial expression and cognitive process characteristics (age, gender, and driving age) were used as the inputs of the proposed model. Convolutional techniques were adopted to construct the model for driver's emotion detection simultaneously considering the driver's facial expression and cognitive process characteristics. A driver's emotion data collection was carried out to validate the performance of the proposed method. The collected dataset consists of 40 drivers' frontal facial videos, their cognitive process characteristics, and self-reported assessments of driver emotions. Another two deep networks were also used to compare recognition performance. The results prove that the proposed method can achieve well detection results for different databases on the discrete emotion model and dimensional emotion model, respectively.
Open Access
A comprehensive flight plan risk assessment and optimization method considering air and ground risk of UAM
(IEEE, 2022-10-31) Su, Yu; Xu, Yan; Inalhan, Gokhan
Inspired by risk analysis assistance service and flight plan preparation / optimization service in U-space service, this paper investigates a flight plan risk assessment and optimization method for future urban air mobility. The quantitative risk assessment of the flight plan is divided into two parts: the ground and air risks of the flight plan. After evaluating the risk of the flight plan, optimization suggestions are given to guide the path planning algorithm to optimize the flight plan at low risk. The quantitative risk assessment of the flight plan corresponds to risk analysis assistance service in U-space service, and the procedure to give optimization suggestions correspond to flight plan preparation / optimization service in U-space service. This paper selects the task scenario of logistics drone cargo transportation and carries out risk assessment on the specific flight plan. From the assessment results, when the flight plan crosses the pedestrian intensive area on the ground or the road with high-speed vehicles, the risk value of the corresponding flight plan segment increases significantly. When the flight plan segment approaches the area near the airport or intersects with other UAM participants with the same mission time window, the corresponding risk value is also high. After obtaining the risk assessment results, the targeted optimization suggestions are given to guide the path planning algorithm to optimize the flight plan at low risk. The risk of the optimized flight plan has been significantly reduced.
Open Access
Comprehensive risk assessment and utilization for contingency management of future AAM system
(AIAA, 2023-06-08) Altun, Arinc Tutku; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.
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.
Open Access
Conflict probability based strategic conflict resolution for UAS traffic management
(IEEE, 2023-11-10) Tang, Yiwen; Xu, Yan; Inalhan, Gokhan
In this paper, we present a strategic conflict resolution method based on the conflict probability estimation, in the context of Unmanned Aircraft System (UAS) Traffic Management. We first elaborate a classic approach for flight trajectory generation in a designated realistic airspace environment, which is then smoothed by B-spline algorithm to achieve higher realism. The trajectories are extended to 4-dimensional Operational Volumes (OV) following the current UTM development visions. This forms the basis for performing a coarse conflict screening process, as the initial part for conflict detection, primarily based on identifying any OVs overlapping in temporal and spatial. Next, we look into the captured OVs and apply a well-studied conflict probability estimation approach, which contributes to a refined and more accurate conflict detection outcome. To resolve the potential conflicts, we propose two models including First-Come, First-Served (FCFS) and optimisation, both embedded with the probability-based conflict detection. In the FCFS approach, flights are delayed in the order of their submission, while the optimisation model aims at cherry-picking flights to seek the optimal solution. Numerical experiments with various case studies are performed to assess the effects with and without such probability concern, as well as different implementation strategies in real world. Results suggest that, allowing OVs’ overlapping to some extent does not necessarily incur conflict over an acceptable probability, whereas the efficiency of airspace use could be improved.
Open Access
Contingency management concept generation for U-space system
(IEEE, 2022-05-12) Altun, Arinc Tutku; Xu, Yan; Inalhan, Gokhan; Vidal-Franco, Ignacio; Hardt, Michael
Contingency management in aviation is a vital concept that ensures safety, security, and efficiency in operations. To fully benefit from the envisioned Advanced Air Mobility system, the need of a structured and system-wide contingency planning will be even more important since the air transportation system paradigm will shift into a highly automated system that includes high-density traffic. The complexity will increase considerably by enlarging the operations to the underserved urban areas. Therefore, the new system needs to provide a more agile, accessible, and flexible environment. In this paper, the need of a contingency management from a holistic approach is described and the base requirements to build such a system are defined by considering the roles and responsibilities of each stakeholder that are defined for the U-space system. Alongside the defined requirements, the tasks of the stakeholders and the expected main contingency sources are explained to have a better understanding of the system. The objective of this work is to provide the base guidelines that help to set appropriate actions by relevant stakeholder under an adverse condition which might compromise the safety and security of the operations within the air traffic network.
Open Access
Demand and capacity balancing technology based on multi-agent reinforcement learning
(IEEE, 2021-11-15) Chen, Yutong; Xu, Yan; Hu, Minghua; Yang, Lei
To effectively solve Demand and Capacity Balancing (DCB) in large-scale and high-density scenarios through the Ground Delay Program (GDP) in the pre-tactical stage, a sequential decision-making framework based on a time window is proposed. On this basis, the problem is transformed into Markov Decision Process (MDP) based on local observation, and then Multi-Agent Reinforcement Learning (MARL) method is adopted. Each flight is regarded as an independent agent to decide whether to implement GDP according to its local state observation. By designing the reward function in multiple combinations, a Mixed Competition and Cooperation (MCC) mode considering fairness is formed among agents. To improve the efficiency of MARL, we use the double Q-Learning Network (DQN), experience replay technology, adaptive ϵ-greedy strategy and Decentralized Training with Decentralized Execution (DTDE) framework. The experimental results show that the training process of the MARL method is convergent, efficient and stable. Compared with the Computer-Assisted Slot Allocation (CASA) method used in the actual operation, the number of flight delays and the average delay time is reduced by 33.7% and 36.7% respectively.
Open Access
Demonstrating advanced U-space services for urban air mobility in a co-simulation environment
(2022-10-08) Fremond, Rodolphe; Tang, Yiwen; Bhundoo, Prithiviraj; Su, Yu; Tutku, Arinc; Xu, Yan; Inalhan, Gokhan
The present paper formalises the development of a co-simulation environment aimed at demonstrating a number of advanced U-space services for the Air Mobility Urban - Large Experimental Demonstrations (AMU-LED) project. The environment has a visionary build that addresses Urban Air Mobility (UAM) challenges to support the High/Standard Performance Vehicles (HPV/SPV) operations within a complex urban environment by proposing an integrated solution that packages advanced services from the pre-flight to the in-flight phase in line with ongoing UAM Concept of Operations (ConOps). This setup opts for a holistic approach by promoting intelligent algorithmic design, artificial intelligence, robust serviceability through either virtual and live elements, and strong cooperation between the different services integrated, in addition to sustain interoperability with external U-space Service providers (USSP), Common Information Service providers (CISPs), and Air Traffic Controllers. The prototype has been recently showcased through the AMU-LED Cranfield (UK) demonstration activities.
Open Access
Developing a digital twin for testing multi-agent systems in advanced air mobility: a case study of Cranfield University and airport
(IEEE, 2023-11-10) Conrad, Christopher; Delezenne, Quentin; Mukherjee, Anurag; Mhowwala, Ali Asgher; Ahmed, Mohammad; Zhao, Junjie; Xu, Yan; Tsourdos, Antonios
Emerging unmanned aircraft system (UAS) and advanced air mobility (AAM) ecosystems rely on the development, certification and deployment of new and potentially intelligent technologies and algorithms. To promote a more efficient development life cycle, this work presents a digital twin architecture and environment to support the rapid prototyping and testing of multi-agent solutions for UAS and AAM applications. It leverages the capabilities of Microsoft AirSim and Cesium as plugins within the Unreal Engine 3D visualisation tool, and consolidates the digital environment with a flexible and scalable Python-based architecture. Moreover, the architecture supports hardware-in-the-loop (HIL) and mixed-reality features for enhanced testing capabilities. The system is comprehensively documented and demonstrated through a series of use cases, deployed within a custom digital environment, comprising both indoor and outdoor areas at Cranfield University and Airport. These include collaborative surveillance, UTM flight authorisation and UTM conformance monitoring experiments, that showcase the modularity, scalability and functionality of the proposed architecture. All 3D models and experimental observations are critically evaluated and shown to exhibit promising results. This thereby represents a critical step forward in the development of a robust digital twin for UAS and AAM applications.
Open Access
Developing a stackable programme based on the advanced air mobility systems MSc course
(Elsevier BV, 2024-09-05) Zhao, Junjie; Gong, Tingyu; Nnamani, Christantus; Conrad, Christopher; Fremond, Rodolphe; Tang, Yiwen; Xu, Yan; Tsourdos, Antonios
This study proposes the development of content and materials for a stackable programme that aligns with the existing Cranfield University Advanced Air Mobility Systems (AAMS) MSc Course and integrates with ongoing Future Flight Challenge (FFC) projects, emerging research and development (R&D) capacities, and the growing demand for skilled professionals in the sector. The programme is structured into four phases: enhancement of taught modules through technology-enhanced teaching (TET), enrichment of project-based learning, bolstering of student experience and career development, and a stackable approach adaptable to various educational levels. This approach was evaluated using courses from the 2022/23 and 2023/24 academic years.
Open Access
The development of an advanced air mobility flight testing and simulation infrastructure
(MDPI, 2023-08-17) Altun, Arinc Tutku; Hasanzade, Mehmet; Saldiran, Emre; Guner, Guney; Uzun, Mevlut; Fremond, Rodolphe; Tang, Yiwen; Bhundoo, Prithiviraj; Su, Yu; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.; Fransoy, Alejandro; Modha, Ajay; Tena, Jose Antonio; Nieto, Cesar; Vilaplana, Miguel; Tojal, Marta; Gordo, Victor; Mendendez, Pablo; Gonzalez, Ana
The emerging field of Advanced Air Mobility (AAM) holds great promise for revolutionizing transportation by enabling the efficient, safe, and sustainable movement of people and goods in urban and regional environments. AAM encompasses a wide range of electric vertical take-off and landing (eVTOL) aircraft and infrastructure that support their operations. In this work, we first present a new airspace structure by considering different layers for standard-performing vehicles (SPVs) and high-performing vehicles (HPVs), new AAM services for accommodating such a structure, and a holistic contingency management concept for a safe and efficient traffic environment. We then identify the requirements and development process of a testing and simulation infrastructure for AAM demonstrations, which specifically aim to explore the decentralized architecture of the proposed concept and its use cases. To demonstrate the full capability of AAM, we develop an infrastructure that includes advanced U-space services, real and simulated platforms that are suitable for future AAM use cases such as air cargo delivery and air taxi operations, and a co-simulation environment that allows all of the AAM elements to interact with each other in harmony. The considered infrastructure is envisioned to be used in AAM integration-related efforts, especially those focusing on U-space service deployment over a complex traffic environment and those analyzing the interaction between the operator, the U-space service provider (USSP), and the air traffic controller (ATC).
Open Access
A digital twin mixed-reality system for testing future advanced air mobility concepts: a prototype
(IEEE, 2023-05-15) Zhao, Junjie; Conrad, Christopher; Delezenne, Quentin; Xu, Yan; Tsourdos, Antonios
The UK Future Flight Vision and Roadmap defines how aviation in the UK is envisioned to develop by 2030. As part of the Future Flight demonstration segment, project HADO (High-intensity Autonomous Drone Operations) will develop, test, and deploy fully automated Unmanned Aircraft System (UAS) operations at London Heathrow airport. The resource-demanding nature of real-world tests, however, suggests that developing and improving the reliability and efficiency of virtual environment-based testing methods is indispensable for the evolution of such operations. Nonetheless, developing a high-fidelity and real-time virtual environment that enables the safe, scalable, and sustainable development, verification, and validation of UAS operations remains a daunting task. Notably, the need to integrate physical and virtual elements with a high degree of correlation presents a significant challenge. Consequently, as part of the synthetic test environment work package within the HADO project, this paper proposes a Digital Twin (DT) system to enable mixed-reality tests in the context of autonomous UAS operations. This connects a physical world to its digital counterpart made up of five distinct layers and several digital elements to support enhanced mixed-reality functionality. The paper highlights how the static layers of the synthetic test environment are built, and presents a DT prototype that supports mixed-reality test capabilities. In particular, the ability to inject virtual obstacles into physical test environments is demonstrated, highlighting how the sharp boundaries between virtual environments and reality can be blurred for safe, flexible, efficient, and effective testing of UAS operations.
Open Access
Dynamic separation minima prediction with collision risk modelling (CRM)
(IEEE, 2023-11-10) Nnamani, Christantus O.; Gong, Tingyu; Xu, Yan; Tsourdos, Antonios
In this paper, we modelled the geometry between 2 proximate aircraft as an oblate-spheroid and obtained a collision risk model based on collision probability. The methodology entails translating the communication, navigation and surveillance error characteristics, and wind uncertainty into the spatial domain of spheroid. Furthermore, we used the collision probability to design a dynamic separation minima based on the parameters of the oblate-spheroid geometry. The results showed that by varying the parameters of the spheroid, allows for a dynamic setting of the separation minima. The collision probability was compared to Monte Carlo simulations as a baseline model. Therefore we proposed a dynamic configuration of the separation minima between aircraft as a function of the collaborative geometry to increase the airspace capacity, especially with great demand from unmanned operations.