摘要 :
Machine learning has proven to be the tool of choice for achieving human-like or even super-human performance with automation on specific tasks. As a result, this data-driven approach is currently experiencing massive interest in ...
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Machine learning has proven to be the tool of choice for achieving human-like or even super-human performance with automation on specific tasks. As a result, this data-driven approach is currently experiencing massive interest in all industry domains. This increased use also applies for the safety critical aviation domain. With no human pilot on board, the potential use cases of machine learning for unmanned aircraft are particularly promising. Even upcoming Urban Air Mobility concepts are planning to remove the onboard pilot and instead use machine learning to support a remote pilot, possibly supervising a fleet of vehicles. However, the verification of machine learning algorithms is a challenging problem, since established safety standards and assurance methods are not applicable. Thus, this work comprises a literature study on the topic of machine learning verification and safety. This research paper uses a systematic approach to map and categorize the research and focuses on specific subtopics that are of particular interest in the context of existing guidance documents.
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The term Urban Air Mobility covers many several applications to meet different transport needs. The cross-institutional and interdisciplinary research project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Cente...
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The term Urban Air Mobility covers many several applications to meet different transport needs. The cross-institutional and interdisciplinary research project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Center (DLR)" brings together a wide variety of departments from the DLR research fields to research on the vision of Urban Air Mobility. This paper describes the five use cases Intra-City, Mega-City, Airport-Shuttle, Sub-Urban and Inter-City, which were defined in order to create a common working basis for the project. In addition to the description of the transport needs, the paper presents technology scenarios, mission profiles, concepts of operation, vehicle configurations and infrastructure related to the use cases. Based on the defined use cases, technical feasibility, efficiency, sustainability, market development potential and social acceptance will be investigated in the course of the project.
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This work proposes a novel risk-based geo-fencing approach. Multiple, adjacent geo-fences are each assigned a specific risk level. An UAS with a low confidence level would be restricted to an area with no or very low risk. However...
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This work proposes a novel risk-based geo-fencing approach. Multiple, adjacent geo-fences are each assigned a specific risk level. An UAS with a low confidence level would be restricted to an area with no or very low risk. However, an UAS with a high confidence level could be allowed to exit such a geo-fence and cross over to another geo-fence with a different risk level. This approach enables different scenarios for the use of geo-fences and requirements for entering, flying, and leaving geo-fences of specific risk. Moreover, using runtime monitoring, the UAS can be assigned a dynamic confidence level, which represents the current and prior system health, system performance, or possibly environmental conditions. This results in a structured methodology for the independent assurance of geo-fences corresponding to specific and possibly dynamic confidence levels of an UAS. The geo-fencing problem as well as the risk-based approach is formalized in the specification language Lola, which provides a concise unambiguous mathematical foundation. Specified properties can be checked at runtime due to automatically generated monitors. This results in a trustworthy implementation, possibly enabling cost-effective UAS operation in accordance to upcoming regulations. Finally, a simulation is used as proof of concept to show the feasibility of the presented approach.
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摘要 :
This work proposes a novel risk-based geo-fencing approach. Multiple, adjacent geo-fences are each assigned a specific risk level. An UAS with a low confidence level would be restricted to an area with no or very low risk. However...
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This work proposes a novel risk-based geo-fencing approach. Multiple, adjacent geo-fences are each assigned a specific risk level. An UAS with a low confidence level would be restricted to an area with no or very low risk. However, an UAS with a high confidence level could be allowed to exit such a geo-fence and cross over to another geo-fence with a different risk level. This approach enables different scenarios for the use of geo-fences and requirements for entering, flying, and leaving geo-fences of specific risk. Moreover, using runtime monitoring, the UAS can be assigned a dynamic confidence level, which represents the current and prior system health, system performance, or possibly environmental conditions. This results in a structured methodology for the independent assurance of geo-fences corresponding to specific and possibly dynamic confidence levels of an UAS. The geo-fencing problem as well as the risk-based approach is formalized in the specification language Lola, which provides a concise unambiguous mathematical foundation. Specified properties can be checked at runtime due to automatically generated monitors. This results in a trustworthy implementation, possibly enabling cost-effective UAS operation in accordance to upcoming regulations. Finally, a simulation is used as proof of concept to show the feasibility of the presented approach.
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Unmanned Aircraft Systems (UAS) with autonomous decision-making capabilities are of increasing interest for a wide area of applications such as logistics and disaster recovery. In order to ensure the correct behavior of the system...
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Unmanned Aircraft Systems (UAS) with autonomous decision-making capabilities are of increasing interest for a wide area of applications such as logistics and disaster recovery. In order to ensure the correct behavior of the system and to recognize hazardous situations or system faults, we applied stream runtime monitoring techniques within the DLR ARTIS (Autonomous Research Testbed for Intelligent System) family of unmanned aircraft. We present our experience from specification elicitation, instrumentation, offline log-file analysis, and online monitoring on the flight computer on a test rig. The debugging and health management support through stream runtime monitoring techniques have proven highly beneficial for system design and development. At the same time, the project has identified usability improvements to the specification language, and has influenced the design of the language.
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摘要 :
Unmanned Aircraft Systems (UAS) with autonomous decision-making capabilities are of increasing interest for a wide area of applications such as logistics and disaster recovery. In order to ensure the correct behavior of the system...
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Unmanned Aircraft Systems (UAS) with autonomous decision-making capabilities are of increasing interest for a wide area of applications such as logistics and disaster recovery. In order to ensure the correct behavior of the system and to recognize hazardous situations or system faults, we applied stream runtime monitoring techniques within the DLR ARTIS (Autonomous Research Testbed for Intelligent System) family of unmanned aircraft. We present our experience from specification elicitation, instrumentation, offline log-file analysis, and online monitoring on the flight computer on a test rig. The debugging and health management support through stream runtime monitoring techniques have proven highly beneficial for system design and development. At the same time, the project has identified usability improvements to the specification language, and has influenced the design of the language.
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This work presents the processes and tools that were installed and developed to validate the ARTIS software and achieve compliance of an unmanned rotorcraft testbed with corresponding standards. A brief introduction to the autonom...
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This work presents the processes and tools that were installed and developed to validate the ARTIS software and achieve compliance of an unmanned rotorcraft testbed with corresponding standards. A brief introduction to the autonomous guidance and navigation capabilities of our unmanned aircraft is given in order to illustrate the software complexity and practical integration challenges introduced by such functionalities. Our software development process is presented which is aimed at a practical balance between exhaustive testing and the rapid integration of new features. It features a greedy integration procedure that is aimed at the preservation of existing features and performances. Automated tests drive the development of our mission planning, mission management and sensor fusion systems. New research code can be integrated such that side effects on existing systems are minimized.
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摘要 :
This work presents the processes and tools that were installed and developed to validate the ARTIS software and achieve compliance of an unmanned rotorcraft testbed with corresponding standards. A brief introduction to the autonom...
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This work presents the processes and tools that were installed and developed to validate the ARTIS software and achieve compliance of an unmanned rotorcraft testbed with corresponding standards. A brief introduction to the autonomous guidance and navigation capabilities of our unmanned aircraft is given in order to illustrate the software complexity and practical integration challenges introduced by such functionalities. Our software development process is presented which is aimed at a practical balance between exhaustive testing and the rapid integration of new features. It features a greedy integration procedure that is aimed at the preservation of existing features and performances. Automated tests drive the development of our mission planning, mission management and sensor fusion systems. New research code can be integrated such that side effects on existing systems are minimized.
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The introduction of machine learning in the aviation domain is an ongoing process. This is also true for safety-critical domains, especially for the area of Urban Air Mobility. A significant growth in number of air taxis and an in...
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The introduction of machine learning in the aviation domain is an ongoing process. This is also true for safety-critical domains, especially for the area of Urban Air Mobility. A significant growth in number of air taxis and an increasing level of autonomy is to be expected allowing for operating a large number of air taxis in complex urban environments. Due to the complexity of the tasks and the environment, key autonomy functions will be realized using machine learning, for example the camera-based detection of objects. However, the safety assurance for avionics systems using machine learning components is challenging. This work investigates safety and verification aspects of machine learning components. A camera-based detection of humans on the ground, e.g. to assess a potential landing area, serves as an example for an machine learning-based autonomy functio and was integrated into an Unmanned Aircraft. In the context of this exemplary machine learning component, the concept of Operational Design Domain as recently adapted European Aviation Safety Agency in the context of machine learning assurance is described along with other key concepts of machine learning assurance. Furthermore, runtime assurance is used to monitor conformance to the Operational Design Domain during flight. The presented flight test results indicate that monitoring the Operational Design Domain can support performance as well as the safety of the operation.
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Unmanned aircraft systems (UAS) have been in civil use for several years. A new risk-based approach to approval was developed by the Joint Authorities for Rulemaking of Unmanned Systems (JARUS) which relies on the so-called Specif...
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Unmanned aircraft systems (UAS) have been in civil use for several years. A new risk-based approach to approval was developed by the Joint Authorities for Rulemaking of Unmanned Systems (JARUS) which relies on the so-called Specific Operations Risk Assessment (SORA) for the specific category- Operational authorization is based on the assessment using the SORA process, which evaluates the safety of the operation and not solely the aircraft design. However, to comply with the resulting mitigations it is necessary to convince authorities using "Acceptable Means of Compliance" (AMC). The goal of the European research project "AW-Drones" is to identify and assess existing standards as a possible AMC for the existing and upcoming regulations. The research in "AW-Drones" is performed by an international consortium of industry and research agencies. Additional stakeholders support the project, including the European Union Aviation Safety Agency (EASA) and other groups of experts, committees, and Standard Development Organizations (SDOs). In this paper, the approach and methodology to identify possible AMC for the SORA is described, including the current state of work. The results of the data collection step and the assessment are outlined. The used criteria are shown and the impact on the SORA process is discussed. An outlook will detail on remaining tasks. The dissemination of the work in a public database is presented that offers the results on AMC assessment directly to a drone operator.
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