Impact of Traffic-Following on Order of Autonomous Airspace Operations

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Auteurs principaux: Jain, Anahita, Idris, Husni R., Clarke, John-Paul
Format: Preprint
Publié: 2024
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author Jain, Anahita
Idris, Husni R.
Clarke, John-Paul
author_facet Jain, Anahita
Idris, Husni R.
Clarke, John-Paul
contents In this paper, we investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically-updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent's traffic-following behavior based on these trade-offs.
format Preprint
id arxiv_https___arxiv_org_abs_2404_17627
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Impact of Traffic-Following on Order of Autonomous Airspace Operations
Jain, Anahita
Idris, Husni R.
Clarke, John-Paul
Multiagent Systems
Computational Engineering, Finance, and Science
Emerging Technologies
Systems and Control
In this paper, we investigate the dynamic emergence of traffic order in a distributed multi-agent system, aiming to minimize inefficiencies that stem from unnecessary structural impositions. We introduce a methodology for developing a dynamically-updating traffic pattern map of the airspace by leveraging information about the consistency and frequency of flow directions used by current as well as preceding traffic. Informed by this map, an agent can discern the degree to which it is advantageous to follow traffic by trading off utilities such as time and order. We show that for the traffic levels studied, for low degrees of traffic-following behavior, there is minimal penalty in terms of aircraft travel times while improving the overall orderliness of the airspace. On the other hand, heightened traffic-following behavior may result in increased aircraft travel times, while marginally reducing the overall entropy of the airspace. Ultimately, the methods and metrics presented in this paper can be used to optimally and dynamically adjust an agent's traffic-following behavior based on these trade-offs.
title Impact of Traffic-Following on Order of Autonomous Airspace Operations
topic Multiagent Systems
Computational Engineering, Finance, and Science
Emerging Technologies
Systems and Control
url https://arxiv.org/abs/2404.17627