User Interaction with Digital Twins for Driving: How Comparable Are Simulated and Real Trajectories?

This paper investigates the physiological responses of individuals driving both on a real route and within a vehicle simulator designed as a digital twin of that route. The analysis of observed data patterns in stress response bio signals provides sufficient evidence of similarity to validating the driving simulation digital twin as a reliable replacement for real-world experiences in controlled and consistent settings, or when overall trends of physiological variables, rather than specific variable levels, are of interest. The findings also stress the need for optimizing the precision of digital twins in complex settings. This study introduces a time-series-based validation approach for driving digital twins by comparing continuous physiological trajectories between real and simulated driving.

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Publication Details

Journal
Systems
Published
2026-01-30
DOI
https://doi.org/10.3390/systems14020144
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

User Interaction with Digital Twins for Driving: How Comparable Are Simulated and Real Trajectories?

Alina M. Chircu, Eldar Dr. Sultanow, Joachim Riedl, Stefan Wengler et al.
Systems
Human-Automation Interaction and Safety
article

User Interaction with Digital Twins for Driving: How Comparable Are Simulated and Real Trajectories?

Alina M. Chircu, Eldar Dr. Sultanow, Joachim Riedl, Stefan Wengler, Christian Czarnecki, Marcin Czaban
article en

Abstract

This paper investigates the physiological responses of individuals driving both on a real route and within a vehicle simulator designed as a digital twin of that route. The analysis of observed data patterns in stress response bio signals provides sufficient evidence of similarity to validating the driving simulation digital twin as a reliable replacement for real-world experiences in controlled and consistent settings, or when overall trends of physiological variables, rather than specific variable levels, are of interest. The findings also stress the need for optimizing the precision of digital twins in complex settings. This study introduces a time-series-based validation approach for driving digital twins by comparing continuous physiological trajectories between real and simulated driving.

SystemsVol. 14(2)
University of New Mexico (US), Capgemini (Netherlands) (NL), Hof University of Applied Sciences (DE), University of Bayreuth (DE), FH Aachen (DE)
Openalex Percentile: Top 77%
Human-Automation Interaction and Safety
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