A Computational Framework for Optimal Adaptive Function Allocation in a Human-Autonomy Teaming Scenario

This article proposes a quantitative framework for optimally allocating task functions in human-autonomy teaming (HAT). HAT involves cooperation between humans and autonomous agents to achieve common goals. As humans and autonomous agents possess different capabilities, function allocation plays a c...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE Open Journal of Control Systems Vol. 3; pp. 32 - 44
Main Authors:	Byeon, Sooyung, Choi, Joonwon, Hwang, Inseok
Format:	Journal Article
Language:	English
Published:	IEEE 2024
Subjects:	Autonomous agents Autonomous systems Computational modeling Computational work model Drones function allocation human-automation interaction human-autonomy teaming Human-machine systems human-vehicle systems Optimization Resource management Task analysis Teamwork
ISSN:	2694-085X, 2694-085X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	This article proposes a quantitative framework for optimally allocating task functions in human-autonomy teaming (HAT). HAT involves cooperation between humans and autonomous agents to achieve common goals. As humans and autonomous agents possess different capabilities, function allocation plays a crucial role in ensuring effective HAT. However, designing the best adaptive function allocation remains a challenge, as existing methods often rely on qualitative rules and intensive human-subject studies. To address this limitation, we propose a computational function allocation approach that leverages cognitive engineering, computational work models, and optimization techniques. The proposed optimal adaptive function allocation method is composed of three main elements: 1) analyze the teamwork to identify a set of all possible function allocations within a team construction, 2) numerically simulate the teamwork in temporal semantics to explore the interaction of the team with complex environments using the identified function allocations in a trial-and-error manner, and 3) optimize the adaptive function allocation with respect to a given situation such as physical conditions, available information resources, and human mental workload. For the optimization, we utilize performance metrics such as task performance, human mental workload, and coherency in function allocations. To illustrate the effectiveness of the proposed framework, we present a simulated HAT scenario involving a human work model and drone fleet for last-mile delivery in disaster relief operations.
AbstractList	This article proposes a quantitative framework for optimally allocating task functions in human-autonomy teaming (HAT). HAT involves cooperation between humans and autonomous agents to achieve common goals. As humans and autonomous agents possess different capabilities, function allocation plays a crucial role in ensuring effective HAT. However, designing the best adaptive function allocation remains a challenge, as existing methods often rely on qualitative rules and intensive human-subject studies. To address this limitation, we propose a computational function allocation approach that leverages cognitive engineering, computational work models, and optimization techniques. The proposed optimal adaptive function allocation method is composed of three main elements: 1) analyze the teamwork to identify a set of all possible function allocations within a team construction, 2) numerically simulate the teamwork in temporal semantics to explore the interaction of the team with complex environments using the identified function allocations in a trial-and-error manner, and 3) optimize the adaptive function allocation with respect to a given situation such as physical conditions, available information resources, and human mental workload. For the optimization, we utilize performance metrics such as task performance, human mental workload, and coherency in function allocations. To illustrate the effectiveness of the proposed framework, we present a simulated HAT scenario involving a human work model and drone fleet for last-mile delivery in disaster relief operations.
Author	Byeon, Sooyung Choi, Joonwon Hwang, Inseok
Author_xml	– sequence: 1 givenname: Sooyung orcidid: 0000-0003-4297-0331 surname: Byeon fullname: Byeon, Sooyung email: sbyeon@purdue.edu organization: School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA – sequence: 2 givenname: Joonwon orcidid: 0000-0001-8470-3528 surname: Choi fullname: Choi, Joonwon email: choi774@purdue.edu organization: School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA – sequence: 3 givenname: Inseok orcidid: 0000-0001-7847-9865 surname: Hwang fullname: Hwang, Inseok email: ihwang@purdue.edu organization: School of Aeronautics and Astronautics, Purdue University, West Lafayette, IN, USA
BookMark	eNpNkN1q4zAQhUVpob9P0F7oBZyVNI5tXZrQtF0KuUgWdq_ESBoHt7YUZGeXvn2dpiy5msNhvsPMuWbnIQZi7F6KmZRC_1j9XKz_rGdKKJgB5EJAfsauVKHzTFTz3-cn-pLdDcObEEJVJahcXLFtzRex3-1HHNsYsOPLhD39i-mdNzHx1W5s-8mtPU7qL_HlPrjDJq-7LroviLeBI3_e9xiyej_GEPsPviHs27Dla0cBUxtv2UWD3UB33_OG_Vo-bhbP2evq6WVRv2YOQI5ZM40SpfbzxpUeldXaV-CsrsgKQluqpvBVpZSe25JAS_AWhazATj9qqeCGvRxzfcQ3s0vT9enDRGzNlxHT1mAaW9eRKaxQE5k7XWFeaG8VKCLvixwclc5NWXDMcikOQ6Lmf54U5lC9OVZvDtWb7-on6uFItUR0QkA-L4sSPgG594NS
CODEN	IOJCD4
Cites_doi	10.1007/s101110200022 10.1145/169891.169998 10.1109/LRA.2023.3285474 10.1109/ACCESS.2017.2746752 10.1057/jos.2010.3 10.1002/9781119857433 10.1177/0018720820960865 10.1016/S1479-3601(02)02003-9 10.1017/aer.2018.14 10.1177/1555343419878038 10.1016/j.ifacol.2023.01.111 10.1145/2667239.2667287 10.1007/978-3-030-78513-0_12 10.1007/978-3-030-44184-5_100113 10.1007/978-3-030-71356-0_6 10.1201/9781410607775.ch8 10.3389/fpsyg.2021.589585 10.1007/978-3-031-18641-7_45 10.1518/001872097778543886 10.2514/1.I010146 10.1201/b12457 10.1177/1555343419869484 10.1145/3603194 10.1016/j.sheji.2016.09.001 10.1016/j.ergon.2012.03.004 10.1109/TSMC.1983.6313160 10.1109/MIS.2013.70 10.1518/001872095779049543 10.2514/1.I010147 10.1109/MCS.2020.3019721 10.1109/JSYST.2019.2918283 10.1109/3468.844354 10.1016/j.ijdrr.2018.02.020 10.1177/1555343413490166 10.1518/155534308X284417 10.1109/MIS.2014.87 10.1201/9781315572543 10.1145/3341568.3342111
ContentType	Journal Article
DBID	97E ESBDL RIA RIE AAYXX CITATION DOA
DOI	10.1109/OJCSYS.2023.3340034
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE Xplore Open Access Journals (WRLC) IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef DOAJ: Directory of Open Access Journal (DOAJ)
DatabaseTitle	CrossRef
DatabaseTitleList
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2694-085X
EndPage	44
ExternalDocumentID	oai_doaj_org_article_6b021834c98a469db232eedd643ce7cc 10_1109_OJCSYS_2023_3340034 10345767
Genre	orig-research
GrantInformation_xml	– fundername: NSF grantid: CNS-1836952
GroupedDBID	0R~ 97E ABVLG ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ EBS ESBDL GROUPED_DOAJ JAVBF M~E OCL OK1 RIA RIE AAYXX CITATION
ID	FETCH-LOGICAL-c331t-fc337a19d5fc7da2b99d83cb98eb0eab72f6d882295b7e3913dba0183b2699123
IEDL.DBID	DOA
ISICitedReferencesCount	1
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001328726800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2694-085X
IngestDate	Fri Oct 03 12:53:35 EDT 2025 Sat Nov 29 06:02:59 EST 2025 Wed Aug 27 01:58:05 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Language	English
License	https://creativecommons.org/licenses/by/4.0/legalcode
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c331t-fc337a19d5fc7da2b99d83cb98eb0eab72f6d882295b7e3913dba0183b2699123
ORCID	0000-0001-8470-3528 0000-0001-7847-9865 0000-0003-4297-0331
OpenAccessLink	https://doaj.org/article/6b021834c98a469db232eedd643ce7cc
PageCount	13
ParticipantIDs	crossref_primary_10_1109_OJCSYS_2023_3340034 ieee_primary_10345767 doaj_primary_oai_doaj_org_article_6b021834c98a469db232eedd643ce7cc
PublicationCentury	2000
PublicationDate	20240000 2024-00-00 2024-01-01
PublicationDateYYYYMMDD	2024-01-01
PublicationDate_xml	– year: 2024 text: 20240000
PublicationDecade	2020
PublicationTitle	IEEE Open Journal of Control Systems
PublicationTitleAbbrev	OJCSYS
PublicationYear	2024
Publisher	IEEE
Publisher_xml	– name: IEEE
References	ref13 ref35 ref12 ref34 ref15 ref37 ref14 ref36 ref31 ref30 ref11 ref33 ref10 ref32 ref2 ref1 ref17 ref39 ref16 ref38 ref19 Johnson (ref3) 2018 ref18 Sutton (ref40) 2018 ref24 ref23 ref26 ref25 ref20 Fitts (ref7) 1951 ref41 ref22 ref21 ref28 ref27 ref29 ref8 ref9 ref4 ref6 ref5
References_xml	– ident: ref10 doi: 10.1007/s101110200022 – ident: ref9 doi: 10.1145/169891.169998 – ident: ref23 doi: 10.1109/LRA.2023.3285474 – ident: ref39 doi: 10.1109/ACCESS.2017.2746752 – start-page: 1 volume-title: Proc. Symp. Hum. Autonomy Teaming year: 2018 ident: ref3 article-title: Understanding human-autonomy teaming through interdependence analysis – ident: ref15 doi: 10.1057/jos.2010.3 – ident: ref18 doi: 10.1002/9781119857433 – ident: ref1 doi: 10.1177/0018720820960865 – ident: ref4 doi: 10.1016/S1479-3601(02)02003-9 – ident: ref30 doi: 10.1017/aer.2018.14 – ident: ref5 doi: 10.1177/1555343419878038 – ident: ref22 doi: 10.1016/j.ifacol.2023.01.111 – ident: ref34 doi: 10.1145/2667239.2667287 – ident: ref24 doi: 10.1007/978-3-030-78513-0_12 – ident: ref19 doi: 10.1007/978-3-030-44184-5_100113 – ident: ref26 doi: 10.1007/978-3-030-71356-0_6 – ident: ref11 doi: 10.1201/9781410607775.ch8 – ident: ref2 doi: 10.3389/fpsyg.2021.589585 – ident: ref25 doi: 10.1007/978-3-031-18641-7_45 – ident: ref31 doi: 10.1518/001872097778543886 – volume-title: Reinforcement Learning: An Introduction year: 2018 ident: ref40 – ident: ref12 doi: 10.2514/1.I010146 – ident: ref14 doi: 10.1201/b12457 – ident: ref13 doi: 10.1177/1555343419869484 – ident: ref21 doi: 10.1145/3603194 – ident: ref38 doi: 10.1016/j.sheji.2016.09.001 – ident: ref36 doi: 10.1016/j.ergon.2012.03.004 – ident: ref37 doi: 10.1109/TSMC.1983.6313160 – ident: ref16 doi: 10.1109/MIS.2013.70 – ident: ref29 doi: 10.1518/001872095779049543 – ident: ref33 doi: 10.2514/1.I010147 – ident: ref20 doi: 10.1109/MCS.2020.3019721 – ident: ref41 doi: 10.1109/JSYST.2019.2918283 – ident: ref8 doi: 10.1109/3468.844354 – ident: ref27 doi: 10.1016/j.ijdrr.2018.02.020 – ident: ref17 doi: 10.1177/1555343413490166 – ident: ref35 doi: 10.1518/155534308X284417 – ident: ref6 doi: 10.1109/MIS.2014.87 – volume-title: Human Engineering for an Effective Air Navigation and Traffic Control System year: 1951 ident: ref7 – ident: ref32 doi: 10.1201/9781315572543 – ident: ref28 doi: 10.1145/3341568.3342111
SSID	ssj0002873240
Score	2.2501147
Snippet	This article proposes a quantitative framework for optimally allocating task functions in human-autonomy teaming (HAT). HAT involves cooperation between humans...
SourceID	doaj crossref ieee
SourceType	Open Website Index Database Publisher
StartPage	32
SubjectTerms	Autonomous agents Autonomous systems Computational modeling Computational work model Drones function allocation human-automation interaction human-autonomy teaming Human-machine systems human-vehicle systems Optimization Resource management Task analysis Teamwork
SummonAdditionalLinks	– databaseName: IEEE Electronic Library (IEL) dbid: RIE link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELZoxQADzyLKSx4YSUli147HUFEhhACpBcEU-XFBlWiKoOX3c3ZCBQMDUyzHsi1f7Pvu4vuOkFMDEFsEohFD9RJxzvuRVmUSlQ7fCMVcP-QieLyRt7fZ05O6b4LVQywMAITLZ9DzxfAv383swrvKcIczjvhYtkhLSlkHay0dKgj9PblcwyyUxOr87noweh71fILwHmPcU7H80j6BpP9XVpWgVIab_5zOFtlo0CPNa3FvkxWodsj6D07BXfKS0zpTQ-Plo8Pv61cU8Sm9wyNi6rtw-s2fdHSIis23pPmr12uhOKmopsG9H-WLeQh7oGPQUxyAjixUaF_POuRheDkeXEVNNoXIMpbMoxIfUifK9UsrnU6NUi5j1qgMTAzayLQULvP8730jgamEOaNj3PEmFQgiU7ZH2tWsgn1CLXDsRqDyM4bbDFSptXApE6WDUgjTJWffq1y81aQZRTA2YlXUQim8UIpGKF1y4SWxbOoZr0MFrnbRbKBCmIDmuFWZRpPeGYSCqN8dIioL0tou6XgJ_RivFs7BH_WHZA3nwGtvyhFpz98XcExW7ed88vF-Ej6tL39FzzA priority: 102 providerName: IEEE
Title	A Computational Framework for Optimal Adaptive Function Allocation in a Human-Autonomy Teaming Scenario
URI	https://ieeexplore.ieee.org/document/10345767 https://doaj.org/article/6b021834c98a469db232eedd643ce7cc
Volume	3
WOSCitedRecordID	wos001328726800001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2694-085X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002873240 issn: 2694-085X databaseCode: DOA dateStart: 20220101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2694-085X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002873240 issn: 2694-085X databaseCode: M~E dateStart: 20220101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NT8IwFG8M8aAH4wdG_CA9eHSwraVbj0ggxiiYgAZPS79mMDIIDo_-7b52w4yTFy_bsi1t83tbf--9tL-H0LU0xlfgiHoE6MWjlHY8wdPASzU8YZzojqtF8PIQDYfxdMqfKqW-7JqwQh64AK7NpGNxqngsIJTTElwAmNc1MKkykVJ29gWvpxJMvbuUUWSV5kqZocDn7dF9b_w6btlq4S1CqNVl2aIip9i_VWLFMczgEB2UriHuFkM6QjsmO0b7FcHAE_TWxUUZhjKFhwebtVUYnE88gv9_bpvQYmmnMTwA1rJv4u6HJS13OcuwwC5373XXudvTgCdGzKEDPFYmg-B5UUfPg_6kd-eVpRI8RUiQeymcIhFw3UlVpEUoOdcxUZLHRvpGyChMmY6tuHtHRobwgGgpfMBVhgw8xJCcolq2yMwZwspQaIYBs0lJVWx4KgTTIWGpNiljsoFuNqgly0IRI3GRhM-TAuTEgpyUIDfQrUX291UrZ-1ugJGT0sjJX0ZuoLq1S6U_QiFQis7_o_ELtAcDpkVe5RLV8tXaXKFd9ZXPPldN913B8fG733S7A38AuUHUKQ
linkProvider	Directory of Open Access Journals
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT9wwEB7xqAQcgNJFLK_60GOzTWLHiY8LYgV0WSrtFtFT5McEIUEWwS6_n7ETEBx64BTLsWzLE3u-mXi-AfhhEGNLQDTipF4iIUQWaVUlUeXojVTcZSEXwdUwH42K62v1pw1WD7EwiBgun2HPF8O_fDe1c-8qox3OBeHjfBGWMyHSpAnXenOpEPj39HItt1ASq1-X58fjf-OeTxHe41x4MpYP-ifQ9H_IqxLUymDjkxPahPUWP7J-I_CvsID1Fqy9YxX8Bjd91uRqaP18bPB6AYsRQmWXdEjc-y6cfvBnHRuQavMtWf_Oa7ZQvK2ZZsHBH_XnsxD4wCao72kANrZYk4U97cDfwcnk-DRq8ylElvNkFlX0yHWiXFbZ3OnUKOUKbo0q0MSoTZ5W0hWeAT4zOXKVcGd0THvepJJgZMq3Yame1rgDzKKgbiSpP2OELVBVWkuXclk5rKQ0Xfj5usrlQ0ObUQZzI1ZlI5TSC6VshdKFIy-Jt6ae8zpU0GqX7RYqpQl4TlhVaDLqnSEwSBreEaaymFvbhY6X0LvxGuHs_qf-O6ycTi6G5fBs9HsPVmk-ovGt7MPS7HGOB_DFPs9unx4Pw2f2AmwF0nc
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Computational+Framework+for+Optimal+Adaptive+Function+Allocation+in+a+Human-Autonomy+Teaming+Scenario&rft.jtitle=IEEE+Open+Journal+of+Control+Systems&rft.au=Byeon%2C+Sooyung&rft.au=Choi%2C+Joonwon&rft.au=Hwang%2C+Inseok&rft.date=2024&rft.issn=2694-085X&rft.eissn=2694-085X&rft.volume=3&rft.spage=32&rft.epage=44&rft_id=info:doi/10.1109%2FOJCSYS.2023.3340034&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_OJCSYS_2023_3340034
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2694-085X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2694-085X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2694-085X&client=summon