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.
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 preflight 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.
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.
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.
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