Evidence map›Paper›PMID 40050349›Full record

ArticleScientific reports2025

Passenger physiology in self-driving vehicles during unexpected events.

Zsolt Palatinus, Miklós Lukovics, Márta Volosin, Zsolt Dudás, Szabolcs Prónay, Zoltán Majó-Petri, Henrietta Lengyel, Zsolt Szalay

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Zsolt PalatinusDepartment of Neuroscience and Cognition, Institute of Psychology, University of Szeged, Egyetem utca 2, Szeged, 6722, Hungary. palatinus.zsolt.ferenc@szte.hu.
Miklós LukovicsDepartment of Economic Development, Faculty of Economics and Business Administration, University of Szeged, Szeged, Hungary. miki@eco.u-szeged.hu.
Márta VolosinDepartment of Neuroscience and Cognition, Institute of Psychology, University of Szeged, Egyetem utca 2, Szeged, 6722, Hungary.
Zsolt DudásDepartment of Neuroscience and Cognition, Institute of Psychology, University of Szeged, Egyetem utca 2, Szeged, 6722, Hungary.
Szabolcs PrónayDepartment of Business Studies, Faculty of Economics and Business Administration, University of Szeged, Szeged, Hungary.
Zoltán Majó-PetriDepartment of Business Studies, Faculty of Economics and Business Administration, University of Szeged, Szeged, Hungary.
Henrietta LengyelDepartment of Automotive Technologies, Budapest University of Technology and Economics, Budapest, Hungary.
Zsolt SzalayDepartment of Automotive Technologies, Budapest University of Technology and Economics, Budapest, Hungary.

Funding

Nemzeti Kutatási Fejlesztési és Innovációs Hivatal OTKA K137571
6 · The paper itself

Abstract

While using fully autonomous vehicles is expected to radically change the way we live our daily lives, it is not yet available in most parts of the world, so we only have sporadic results on passenger reactions. Furthermore, we have very limited insights into how passengers react to an unexpected event during the ride. Previous physiological research has shown that passengers have lower levels of anxiety in the event of a human-driven condition compared to a self-driving condition. The aim of our current study was to investigate these differences in unexpected road events in real-life passenger experiences. All subjects were driven through a closed test track in human-driven and then self-driving mode. During the journey, unforeseen obstacles were encountered on the path (deer and human-shaped dummies appeared). Using physiological measurements (EEG, eye movements, head movements and blinking frequencies) our results suggest that passengers had moderate affective preferences for human-driven conditions. Furthermore, multifractal spectra of eye movements and head movements were wider and blinking frequencies were decreased during unexpected events. Our findings further establish real-world physiological measurements as a source of information in researching the acceptance and usage of self-driving technologies.

Indexed as

Automobile DrivingAdultAnxietyBlinkingElectroencephalographyEye MovementsFemaleHead MovementsHumansMaleYoung AdultEEGEye-trackingMultiscale analysisSelf-drivingTechnology acceptanceWearable sensors

Identifiers

PMID40050349
PMCPMC11885648

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.