Browsing by Author "Su, Yu"

Now showing 1 - 8 of 8
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    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.
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    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.
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    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.
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    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.
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    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.
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    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).
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    Risk-based flight planning and management for urban air mobility
    (AIAA, 2022-06-20) Su, Yu; Xu, Yan
    This paper investigates a quantitative ground risk assessment method for future urban airmobility, which can be divided into three main processes: risk modelling, risk assessment andmitigation recommendation for flight planning and management. First, the aircraft kineticmodels for both fixed-wing aircraft and rotorcraft are investigated, along with the correspondingballistic and glide descent mode and the associated wind influence. The probabilistic impact toroad traffic and pedestrians on the ground as a result of potential crash are then derived. Withan assumed crash probability of the aircraft, the initial risk value and distribution are computed,which are used to produce a risk cost map across the mission area. Next, the flight request isprocessed based on such risk map using a common path planning algorithm, minimizing theoverall risk for the flight plan to be generated. Finally, a preliminary case study involving arotorcraft conducting urban cargo transportation service is performed to evaluate the proposedrisk assessment method in a real-world urban environment.
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    A risk-based UAM airspace capacity assessment method using Monte Carlo simulation
    (IEEE, 2023-11-10) Su, Yu; Xu, Yan; Inalhan, Gokhan
    Inspired by risk analysis assistance service and dynamic capacity management service in U-space service, this paper investigates a risk-based UAM airspace capacity assessment method using Monte Carlo simulation for future urban air mobility. The quantitative risk assessment of the flight plan is divided into three parts: the ground / air risks of the flight plan and the mid-air collision risk between UAM. Using the comprehensive risk assessment method, this paper generates several simulation scenarios in the airspace to be evaluated in terms of the type of participants, the presence of the detect and avoid system, and the total number of participants in the airspace, conducts Monte Carlo simulations, and records the simulation data for analysis. Through the analysis of simulation data, it is found that the maximum risk of UAM in airspace increases with the increase of the number of airspace invaders and the total number of UAM. However, the maximum risk of UAM in airspace decreases when the aircraft in airspace contains the detection and avoid system with the same other conditions. Based on simulation data, this paper informatively proposes the concept of a 3D risk surface and a risk-based airspace capacity envelope, using the horizontal surface formed by a specific risk threshold to cut the 3D risk surface to form an airspace capacity envelope, which visually describes the number of aircraft that can be contained in the airspace under a specific risk threshold.