Browsing by Author "Hardt, Michael W."

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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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    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.
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    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.
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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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    Enabling UAVs night-time navigation through mutual information-based matching of event-generated images
    (IEEE, 2023-11-10) Escudero, Naiara; Hardt, Michael W.; Inalhan, Gokhan
    Advanced Air Mobility is expected to revolutionize the future of general transportation. However, to make it a reality, significant challenges arise requiring technologies to ensure the expected attributes in these scenarios: resilience, robustness, large operational range, high accuracy, low SWaP equipment, and real-time processing. Although existing visual-based navigation solutions for aerial applications provide outstanding results under nominal conditions, their performance is highly constrained by the lighting conditions, making them infeasible for real operations. With the main focus of addressing this limitation, and expanding the current operational range to include extreme low-illuminated environments, this paper presents a solution which leverages one of the most powerful properties of event cameras: their high dynamic range. Thus, data provided by an event camera (also called dynamic vision sensor) is used to estimate the relative displacement of a flying vehicle during night-time conditions. To that end, two different threads running in parallel have been developed: a reference map generator, operating at low frequency, focused on reconstructing a 2-D map of the environment, and a localization thread, which matches, at high frequency, real-time event-generated images against the reference map by applying Mutual Information to estimate the aircraft’s relative displacement.
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    Machine learning based visual navigation system architecture for AAM operations with a discussion on its certifiability
    (IEEE, 2022-05-12) Escudero, Naiara; Costas, Pablo; Hardt, Michael W.; Inalhan, Gokhan
    Advanced Air Mobility (AAM) is expected to revolutionize the future of general transportation expanding the conventional notion of air traffic to include several services carried out by autonomous aerial platforms. However, the significant challenges associated with such complex scenarios require the introduction of sophisticated technologies able to deliver the resilience, robustness, and accuracy needed to achieve safe, autonomous operations [39]. In this context, solutions based on Artificial Intelligence (AI), able to overcome some limitations found in traditional approaches, are becoming a major opportunity for the aviation industry, but, at the same time, a significant challenge with respect to the certification standards.With the focal point on further proposing a certifiable architecture for AI-enhanced vision navigation in AAM operations, this paper first, summarizes the current technologies and fusion methods applied to date to navigation purposes, to later address the certification problem. Regarding certification, it explores three specific points: 1) traditional certification procedures; 2) current status of AI homologation recommendations; and 3) other certification factors to be considered for future discussion.
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    Resolution of potential conflicts caused by contingency events in an AAM traffic network
    (IEEE, 2023-05-15) Altun, Arinc Tutku; Baspinar, Baris; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.
    This study presents an approach for pre-flight replanning process to be used in the future Advanced Air Mobility (AAM) system especially after contingency situations and relevant activities take place. The methodology for pre-flight replanning phase is analyzed and modeled in two steps as optimization based potential conflict resolution and demand capacity balancing, which respectively provides safety for the surrounding traffic and efficiency for the traffic network in case of a contingency. These two models can work iteratively to achieve pre-flight replanning for the Unmanned Aircraft System Traffic Management (UTM). The developed pre-flight replanning model can also be used at strategic planning phase. For the use cases, a very large UTM traffic network is considered to have a highly dense traffic environment since the expected complexity is high with the AAM system and to show the efficiency and scalability of the models. Two use cases are examined. First one is about initial flight planning where the conflicted flight plans are safely separated and balance in demand and capacity at vertiports is provided. Second scenario is related to potential conflict resolution for the flights at pre-tactical phase after contingency events observed within the network and demand-capacity balancing after safety related events are resolved. The main objective of this work is to develop a pre-flight replanning service to work compatible with contingency management activities to build the introduced system-wide contingency management concept for the AAM system.
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    RL-based scheduling of an AAM traffic network
    (IEEE, 2023-08-02) Altun, Arinc Tutku; Xu, Yan; Inalhan, Gokhan; Hardt, Michael W.
    This study presents an approach for pre-flight planning process to be used in the future Advanced Air Mobility (AAM) system especially after contingency situations and relevant activities take place. The methodology for scheduling is modeled as a reinforcement learning (RL) agent that resolves potential conflicts for the traffic and balances the demand and capacity at vertiports. The reason behind to use RL is that specific problem requires a very quick response since it also deals with resolving conflicts that are observed between the flights that are about to take-off and the contingent flights that diverted for an emergency landing. The main objective of this work is to develop a pre-flight planning service to work compatible with contingency management activities for enhancing the contingency management process for the AAM system.