Experimental Research on Team Dynamic Function Allocation Strategy Optimization

Chenyuan Yang; Liping Pang; Xin Wang; Ye Deng; Yuan Liu

doi:10.1007/978-981-19-4786-5_5

Experimental Research on Team Dynamic Function Allocation Strategy Optimization

Chenyuan Yang
, Liping Pang^*
, Xin Wang
, Ye Deng
, Yuan Liu

^*Corresponding author for this work

School of Aeronautic Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

This paper mainly focused on the dynamic function allocation strategy proposed by the team, and carries out relevant experimental research. The underwater vehicle consists of three workstations, including Operating Officer (OO), Vehicle Officer (VO) and Leader, was designed and built. Twelve healthy male college-age students were recruited to investigate the effects of two allocation strategies on their mental workload and task performance. Although the result showed that the improvement of Operating Officer’s task performance was less at human-machine allocation strategies than at human-human allocation strategies, the Vehicle Officer’s task performance decreased significantly at human-human allocation strategies. Hence, human-machine collaboration strategy is still the primary scheme at dynamic function allocation based on the convenience of intelligent systems. If the mental workload level and job performance level of Operating Officer are underperforming after the human-machine allocation strategy is completed, part of the Operating Officer’s fault task processing function is assigned to Vehicle Officer.

Original language	English
Title of host publication	Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE
Editors	Shengzhao Long, Balbir S. Dhillon
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	30-36
Number of pages	7
ISBN (Print)	9789811947858
DOIs	https://doi.org/10.1007/978-981-19-4786-5_5
State	Published - 2023
Event	22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022 - Beijing, China Duration: 21 Oct 2022 → 23 Oct 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	941 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022
Country/Territory	China
City	Beijing
Period	21/10/22 → 23/10/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Allocation strategy
Function
Team
Underwater vehicle

Access to Document

10.1007/978-981-19-4786-5_5

Cite this

Yang, C., Pang, L., Wang, X., Deng, Y., & Liu, Y. (2023). Experimental Research on Team Dynamic Function Allocation Strategy Optimization. In S. Long, & B. S. Dhillon (Eds.), Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE (pp. 30-36). (Lecture Notes in Electrical Engineering; Vol. 941 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-4786-5_5

Yang, Chenyuan ; Pang, Liping ; Wang, Xin et al. / Experimental Research on Team Dynamic Function Allocation Strategy Optimization. Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE. editor / Shengzhao Long ; Balbir S. Dhillon. Springer Science and Business Media Deutschland GmbH, 2023. pp. 30-36 (Lecture Notes in Electrical Engineering).

@inproceedings{b43a1cdf19454c8f92c41718fb751e4e,

title = "Experimental Research on Team Dynamic Function Allocation Strategy Optimization",

abstract = "This paper mainly focused on the dynamic function allocation strategy proposed by the team, and carries out relevant experimental research. The underwater vehicle consists of three workstations, including Operating Officer (OO), Vehicle Officer (VO) and Leader, was designed and built. Twelve healthy male college-age students were recruited to investigate the effects of two allocation strategies on their mental workload and task performance. Although the result showed that the improvement of Operating Officer{\textquoteright}s task performance was less at human-machine allocation strategies than at human-human allocation strategies, the Vehicle Officer{\textquoteright}s task performance decreased significantly at human-human allocation strategies. Hence, human-machine collaboration strategy is still the primary scheme at dynamic function allocation based on the convenience of intelligent systems. If the mental workload level and job performance level of Operating Officer are underperforming after the human-machine allocation strategy is completed, part of the Operating Officer{\textquoteright}s fault task processing function is assigned to Vehicle Officer.",

keywords = "Allocation strategy, Function, Team, Underwater vehicle",

author = "Chenyuan Yang and Liping Pang and Xin Wang and Ye Deng and Yuan Liu",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022 ; Conference date: 21-10-2022 Through 23-10-2022",

year = "2023",

doi = "10.1007/978-981-19-4786-5\_5",

language = "英语",

isbn = "9789811947858",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "30--36",

editor = "Shengzhao Long and Dhillon, \{Balbir S.\}",

booktitle = "Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE",

address = "德国",

}

Yang, C, Pang, L, Wang, X, Deng, Y & Liu, Y 2023, Experimental Research on Team Dynamic Function Allocation Strategy Optimization. in S Long & BS Dhillon (eds), Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE. Lecture Notes in Electrical Engineering, vol. 941 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 30-36, 22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022, Beijing, China, 21/10/22. https://doi.org/10.1007/978-981-19-4786-5_5

Experimental Research on Team Dynamic Function Allocation Strategy Optimization. / Yang, Chenyuan; Pang, Liping; Wang, Xin et al.
Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE. ed. / Shengzhao Long; Balbir S. Dhillon. Springer Science and Business Media Deutschland GmbH, 2023. p. 30-36 (Lecture Notes in Electrical Engineering; Vol. 941 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Experimental Research on Team Dynamic Function Allocation Strategy Optimization

AU - Yang, Chenyuan

AU - Pang, Liping

AU - Wang, Xin

AU - Deng, Ye

AU - Liu, Yuan

PY - 2023

Y1 - 2023

N2 - This paper mainly focused on the dynamic function allocation strategy proposed by the team, and carries out relevant experimental research. The underwater vehicle consists of three workstations, including Operating Officer (OO), Vehicle Officer (VO) and Leader, was designed and built. Twelve healthy male college-age students were recruited to investigate the effects of two allocation strategies on their mental workload and task performance. Although the result showed that the improvement of Operating Officer’s task performance was less at human-machine allocation strategies than at human-human allocation strategies, the Vehicle Officer’s task performance decreased significantly at human-human allocation strategies. Hence, human-machine collaboration strategy is still the primary scheme at dynamic function allocation based on the convenience of intelligent systems. If the mental workload level and job performance level of Operating Officer are underperforming after the human-machine allocation strategy is completed, part of the Operating Officer’s fault task processing function is assigned to Vehicle Officer.

AB - This paper mainly focused on the dynamic function allocation strategy proposed by the team, and carries out relevant experimental research. The underwater vehicle consists of three workstations, including Operating Officer (OO), Vehicle Officer (VO) and Leader, was designed and built. Twelve healthy male college-age students were recruited to investigate the effects of two allocation strategies on their mental workload and task performance. Although the result showed that the improvement of Operating Officer’s task performance was less at human-machine allocation strategies than at human-human allocation strategies, the Vehicle Officer’s task performance decreased significantly at human-human allocation strategies. Hence, human-machine collaboration strategy is still the primary scheme at dynamic function allocation based on the convenience of intelligent systems. If the mental workload level and job performance level of Operating Officer are underperforming after the human-machine allocation strategy is completed, part of the Operating Officer’s fault task processing function is assigned to Vehicle Officer.

KW - Allocation strategy

KW - Function

KW - Team

KW - Underwater vehicle

UR - https://www.scopus.com/pages/publications/85137002123

U2 - 10.1007/978-981-19-4786-5_5

DO - 10.1007/978-981-19-4786-5_5

M3 - 会议稿件

AN - SCOPUS:85137002123

SN - 9789811947858

T3 - Lecture Notes in Electrical Engineering

SP - 30

EP - 36

BT - Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE

A2 - Long, Shengzhao

A2 - Dhillon, Balbir S.

PB - Springer Science and Business Media Deutschland GmbH

T2 - 22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022

Y2 - 21 October 2022 through 23 October 2022

ER -

Yang C, Pang L, Wang X, Deng Y, Liu Y. Experimental Research on Team Dynamic Function Allocation Strategy Optimization. In Long S, Dhillon BS, editors, Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE. Springer Science and Business Media Deutschland GmbH. 2023. p. 30-36. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-4786-5_5

Experimental Research on Team Dynamic Function Allocation Strategy Optimization

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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