Automatized Driving Data Analyzer: A Synchronized and Modular Application for Data Logging and Analysis

The Automated Driving Data Analyzer (ADDA) is a modular application written in Python for the synchronized acquisition and analysis of physiological, vehicle, and interface data. It provides a managed data acquisition process and one-click data analysis. It also provides raw data storage and systematic archiving of data sets. ADDA integrates real-time data from a BeamNG vehicle simulation, Pupil Labs eye-tracking system, hand-tracking, and cardiac data. This integration allows the simultaneous recording and analysis of multiple data streams, which can be visualized and controlled through a graphical user interface (GUI) built with Tkinter. The application is designed to help researchers and engineers analyze driving behavior under different conditions, enabling a deeper understanding of the interactions between the driver and automated driving functions.

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Publication Details

Published
2024-11-04
DOI
https://doi.org/10.3390/engproc2024079018
Primary Topic
Traffic Prediction and Management Techniques
Type
article
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article

Automatized Driving Data Analyzer: A Synchronized and Modular Application for Data Logging and Analysis

Viktor Nagy, Ágoston Pál Sándor
Traffic Prediction and Management Techniques
article

Automatized Driving Data Analyzer: A Synchronized and Modular Application for Data Logging and Analysis

Viktor Nagy, Ágoston Pál Sándor
article en

Abstract

The Automated Driving Data Analyzer (ADDA) is a modular application written in Python for the synchronized acquisition and analysis of physiological, vehicle, and interface data. It provides a managed data acquisition process and one-click data analysis. It also provides raw data storage and systematic archiving of data sets. ADDA integrates real-time data from a BeamNG vehicle simulation, Pupil Labs eye-tracking system, hand-tracking, and cardiac data. This integration allows the simultaneous recording and analysis of multiple data streams, which can be visualized and controlled through a graphical user interface (GUI) built with Tkinter. The application is designed to help researchers and engineers analyze driving behavior under different conditions, enabling a deeper understanding of the interactions between the driver and automated driving functions.

Széchenyi István University (HU)
Openalex Percentile: Top 79%
Traffic Prediction and Management Techniques
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