{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T13:10:01Z","timestamp":1747055401986,"version":"3.40.5"},"reference-count":29,"publisher":"American Institute of Aeronautics and Astronautics (AIAA)","issue":"2","content-domain":{"domain":["arc.aiaa.org"],"crossmark-restriction":true},"short-container-title":["Journal of Aerospace Information Systems"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:p> The emergence of Advanced Air Mobility (AAM) has called for novel Air Traffic Management (ATM) solutions to enable the projected high number of operations, particularly in already dense and complex metroplex airspace. Understanding the multidimensional performance impacts of developing air traffic rules, procedures, and services is key to guiding this new traffic management system design. This paper presents a simulation framework to provide a quantitative assessment of the operational performance of ATM services in support of AAM. The framework embeds several modules for high-fidelity modeling of urban air traffic flows based on actual data, ATM service provision, stochastic simulation, and performance quantification. Two key services are analyzed: airspace geofencing and strategic deconfliction. We evaluate the use of these services in a scenario of air mobility operations associated with daily urban commuting in the Sao Paulo metropolitan region. Monte Carlo experiments are performed to simulate the execution of aircraft trajectories managed under different ATM service configurations, allowing for the characterization of operational performance tradeoffs, particularly in terms of safety and efficiency. The work contributes to quantifying the value of novel ATM services for integrating AAM operations in dense metroplex airspace, supporting their design and implementation. <\/jats:p>","DOI":"10.2514\/1.i011469","type":"journal-article","created":{"date-parts":[[2024,10,8]],"date-time":"2024-10-08T16:12:46Z","timestamp":1728403966000},"page":"116-129","update-policy":"https:\/\/doi.org\/10.2514\/aiaa_crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Characterizing Performance Tradeoffs from Air Traffic Management Services for Advanced Air Mobility"],"prefix":"10.2514","volume":"22","author":[{"given":"Mayara Cond\u00e9 Rocha","family":"Mur\u00e7a","sequence":"first","affiliation":[{"name":"Aeronautics Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wallace Silva Sant\u2019Anna","family":"Souza","sequence":"additional","affiliation":[{"name":"Aeronautics Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jo\u00e3o Vitor Turchetti","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Aeronautics Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1387","reference":[{"key":"r1","doi-asserted-by":"publisher","DOI":"10.3390\/su13137421"},{"volume-title":"Urban Air Mobility Airspace Integration Concepts: Operational Concepts and Exploration Approaches","year":"2019","author":"Lascara B.","key":"r2"},{"volume-title":"Urban Air Traffic Management: Concepts of Operations, EmbraerX and Airservices Australia","year":"2020","key":"r3"},{"volume-title":"Unmanned Aircraft System (UAS) Traffic Management (UTM) Concept of Operations v2.0","year":"2020","key":"r4"},{"volume-title":"U-Space Concept of Operations","year":"2019","key":"r5"},{"volume-title":"U-Space Concept of Operations,","year":"2022","key":"r6"},{"volume-title":"Urban Air Mobility Concept of Operations v2.0","year":"2023","key":"r7"},{"key":"r8","doi-asserted-by":"publisher","DOI":"10.3390\/app12020576"},{"key":"r9","unstructured":"\u201cConcept of Operations for Sustainable Urban Air Mobility in Rio de Janeiro,\u201d Eve Air Mobility, 2022, https:\/\/eveairmobility.com\/wp-content\/uploads\/2022\/05\/EveConopsRJ.pdf [retrieved 1 June 2023]."},{"edition":"1","volume-title":"Global Air Traffic Management Operational Concept","year":"2005","key":"r10"},{"volume-title":"Vision for Trajectory-Based Operations","year":"2017","key":"r11"},{"key":"r13","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2021.103324"},{"key":"r14","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2022.103666"},{"key":"r15","doi-asserted-by":"publisher","DOI":"10.1007\/s10846-022-01784-0"},{"key":"r19","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.10.021"},{"key":"r20","doi-asserted-by":"publisher","DOI":"10.1016\/j.paerosci.2021.100726"},{"key":"r21","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.05.001"},{"key":"r22","doi-asserted-by":"publisher","DOI":"10.2514\/1.D0183"},{"key":"r25","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2021.103274"},{"key":"r28","doi-asserted-by":"publisher","DOI":"10.1287\/opre.46.3.406"},{"key":"r29","doi-asserted-by":"publisher","DOI":"10.1287\/opre.1100.0899"},{"key":"r30","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2020.02.012"},{"key":"r31","doi-asserted-by":"publisher","DOI":"10.1016\/j.jairtraman.2018.06.009"},{"key":"r32","doi-asserted-by":"publisher","DOI":"10.1016\/j.jairtraman.2020.102017"},{"key":"r36","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2020.10.039"},{"key":"r39","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2016.2582144"},{"volume-title":"Mixture Models: Inference and Applications to Clustering","year":"1988","author":"McLachlan G. 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