Work

Workload Estimation for a Military Ground Vehicle Crew using Supervised Machine Learning of FACS Action Unit Intensity Data

Year: 2025

Type: article

Source: SAE International Journal of Advances and Current Practices in Mobility

DOI: 10.4271/2025-01-8340

Authors: Christopher Mikulski, Kayla Riegner

Institutions: United States Department of the Army, United States Army Combat Capabilities Development Command, U.S. Army Combat Capabilities Development Command Ground Vehicle System Center

Language: English

Topic: Human-Automation Interaction and Safety

Subfield: Social Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4409018513

FWCI:

Cites: 7

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Related to: 10