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A Dynamic Bayesian-Based Method for DFA in Specialized Vehicles

delete2025-09-22
delete0
PRE
AI
X
Xinyan Li *
J
Jianjie Chu *
X
Xinyu Liu *
F
Feilong Li
DOI：10.1080/10447318.2025.2558019delete
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Abstract

Abstract

En 中文
In specialized vehicles’ confined spaces, human performance is affected by both complex tasks and harsh environments, making task or workload assessments insufficient. This paper categorizes human-machine system (HMS) performance into accuracy and speed, aligning with task requirements. A Dynamic Bayesian Network (DBN) model, based on expert knowledge, is proposed to compute performance under fluctuating task demands. A simplified OpenMATB case study validated the model’s accuracy. Applying dynamic function allocation (DFA) significantly improved HMS performance, guiding automated system design in such constrained settings.
Keywords:
Human-machine function allocation
dynamic Bayesian networks
system performance prediction
specialized vehicles

Journal

I
International Journal of Human-Computer Interaction
IF:
4.9
Papers:
4.5K
Citations:
1.2W

Organization

T
tianjin university
Scholars:
8.0W
Papers: 5.8W
Citations: 88
N
Northwestern Polytechnical University
Scholars:
4.6W
Papers: 3.7W
Citations: 5.3W
Cited Papers

Cited Papers

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