The Relationships among Workload, Automation Reliance, and Human Errors in Safety-Critical Monitoring Roles

This repository contains the R code for our study on the interplay between human workload, automation usage, and error rates in safety-critical socio-technical systems. Despite the increasing use of automation to reduce human workload, human error remains a major contributor to operational failures—especially in high-stakes environments like railway traffic control.

• Link to paper: https://www.sciencedirect.com/science/article/pii/S0925753524003655?via%3Dihub
• Citation: Liu N., Triantis, K., Madsen, P., & Roets, B. (2025). The Relationships among Workload, Automation Reliance, and Human Errors in Safety-Critical Monitoring Roles. Safety Science, 185, 106775. https://doi.org/10.1016/j.ssci.2024.106775

Getting Started

The clean code is in the src folder.

Prerequisites

Before you begin, ensure you have met the following requirements:

• You have installed R and RStudio.
• You are familiar with basic R operations and package management.

This project uses renv for dependency management. The renv package ensures that this project runs with the correct versions of R packages, making it easier to manage project dependencies and share the project with others.

Setting Up the Project

To set up the project on your local machine:

1. Clone the Repository:

   First, clone this repository to your local machine:

   git clone https://github.com/georgia-max/AdoptToAutomation.git

   Second, install 'renv'. If you haven't already installed renv, you can do so by running the following in your R console:

   install.packages("renv")
   

   Third, restore dependencies, Navigate to the project directory and run the following in your R console:

   renv::restore()
   

   This command will install all the necessary R packages as specified in the renv.lock file, ensuring you have the correct package versions required for this project.

Using the Project

First, run the data_prepare.R file to get the preprocessed dataset. Second, run the main.R file to get the regression results.

Notes:

1. Currently, the data anlaysis is performed in this dataset: CRIPTON_60_MINUTES_anonymized_all.csv