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 uatm


Dialogue Possibilities between a Human Supervisor and UAM Air Traffic Management: Route Alteration

Kim, Jeongseok, Kim, Kangjin

arXiv.org Artificial Intelligence

This paper introduces a novel approach to detour management in Urban Air Traffic Management (UATM) using knowledge representation and reasoning. It aims to understand the complexities and requirements of UAM detours, enabling a method that quickly identifies safe and efficient routes in a carefully sampled environment. This method implemented in Answer Set Programming uses non-monotonic reasoning and a two-phase conversation between a human manager and the UATM system, considering factors like safety and potential impacts. The robustness and efficacy of the proposed method were validated through several queries from two simulation scenarios, contributing to the symbiosis of human knowledge and advanced AI techniques. The paper provides an introduction, citing relevant studies, problem formulation, solution, discussions, and concluding comments.


We, Vertiport 6, are temporarily closed: Interactional Ontological Methods for Changing the Destination

Woo, Seungwan, Kim, Jeongseok, Kim, Kangjin

arXiv.org Artificial Intelligence

This paper presents a continuation of the previous research on the interaction between a human traffic manager and the UATMS. In particular, we focus on the automation of the process of handling a vertiport outage, which was partially covered in the previous work. Once the manager reports that a vertiport is out of service, which means landings for all corresponding agents are prohibited, the air traffic system automates what it has to handle for this event. The entire process is simulated through knowledge representation and reasoning. Moreover, two distinct perspectives are respected for the human supervisor and the management system, and the related ontologies and rules address their interactions. We believe that applying non-monotonic reasoning can verify each step of the process and explain how the system works. After a short introduction with related works, this paper continues with problem formulation, primary solution, discussion, and conclusions.


Agent 3, change your route: possible conversation between a human manager and UAM Air Traffic Management (UATM)

Kim, Jeongseok, Kim, Kangjin

arXiv.org Artificial Intelligence

This work in progress paper provides an example to show a detouring procedure through knowledge representation and reasoning. When a human manager requests a detouring, this should affect the related agents. Through non-monotonic reasoning process, we verify each step to be proceeded and provide all the successful connections of the reasoning. Following this progress and continuing this idea development, we expect that this simulated scenario can be a guideline to build the traffic management system in real. After a brief introduction including related works, we provide our problem formulation, primary work, discussion, and conclusions.