Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios

<div class="section abstract"><div class="htmlview paragraph">The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psychophysiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to advance AD technologies. Physiological signals, including electrocardiographic (ECG) and electroencephalographic (EEG) are acquired synchronously with eye-tracking and instrumented steering wheel signals throughout the entire test. The use of dynamic driving simulation enhances the study’s efficacy, facilitating early-stage development insights crucial for the advancement of AD technologies.</div></div>

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Publication Details

Journal
SAE technical papers on CD-ROM/SAE technical paper series
Published
2025-03-31
DOI
https://doi.org/10.4271/2025-01-8048
Citations
1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.68
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article

Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios

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1 citations
SAE technical papers on CD-ROM/SAE technical paper series
Autonomous Vehicle Technology and Safety
0.68
article

Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios

Andrea Galbiati, Giorgio Previati, Andrea Fossati, Edoardo Sabbioni, Marco Ponti, Gianpiero R M Mastinu, M.G. Signorini, Antonella Somma, Linda Boscaro, Massimiliano Gobbi, Lorenzo Uccello, Luca Subitoni, Veronica De Guglielmo, Leda Mastinu
article en
1 citations

Abstract

<div class="section abstract"><div class="htmlview paragraph">The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psychophysiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to advance AD technologies. Physiological signals, including electrocardiographic (ECG) and electroencephalographic (EEG) are acquired synchronously with eye-tracking and instrumented steering wheel signals throughout the entire test. The use of dynamic driving simulation enhances the study’s efficacy, facilitating early-stage development insights crucial for the advancement of AD technologies.</div></div>

SAE technical papers on CD-ROM/SAE technical paper seriesVol. 1
Vita-Salute San Raffaele University (IT), Politecnico di Milano (IT)
Openalex Percentile: Top 32%
Autonomous Vehicle Technology and Safety
0.68
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