How difficult is it perceived to takeover in a level 3 automated vehicle? Investigation of the ease of use according to task and situational factors.

One goal of automated driving is to mitigate risks by minimising human intervention. However, widespread acceptance of automated vehicles hinges on their perceived ease of use, particularly during takeover scenarios. This online survey investigates the perceived difficulty of takeover in Level 3 Aut...

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Publicado en:Ergonomics Vol. 68; no. 10; pp. 1647 - 1660
Autores principales: Ouddiz, Sharon, Lemercier, Céline
Formato: research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Oct2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2025
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      pub: Taylor & Francis Ltd
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        10.1080/00140139.2024.2431584
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        atl: How difficult is it perceived to takeover in a level 3 automated vehicle? Investigation of the ease of use according to task and situational factors.
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          Ouddiz, Sharon
          Lemercier, Céline
        affil: Cognition, Languages, Language and Ergonomics (CLLE) Laboratory, University of Toulouse - Jean Jaurès, Toulouse, France
      sug:
        subj:
          Autonomous Vehicles
          Automobile Driving Psychosocial Factors
          Automation
          Task Performance and Analysis
          France
          Human
          Male
          Female
          Adult
          Middle Age
          Aged
          Factorial Design
          Psychomotor Performance
          Accidents, Traffic
          Analysis of Variance
          Post Hoc Analysis
          Descriptive Statistics
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
          Female
      ab: One goal of automated driving is to mitigate risks by minimising human intervention. However, widespread acceptance of automated vehicles hinges on their perceived ease of use, particularly during takeover scenarios. This online survey investigates the perceived difficulty of takeover in Level 3 Automated Vehicles, focusing on factors influencing takeover performance such as duration of automated mode and traffic density, as well as Non-Driving-Related Tasks like listening to music or engaging in conversation. Using Anderson's experimental protocol based on Integrated Information Theory, 235 drivers aged 18–72 rated takeover difficulty across 32 realistic scenarios varying in these factors. Results indicate significant impacts of all factors on takeover perception, identifying three distinct driver profiles: takeover averse, adaptive, and confident. Findings underscore implications for vehicle acceptance and risk management in automated driving. PRACTITIONER SUMMARY: This study examines perceived takeover difficulty in Level 3 automated vehicles through an online survey of 235 drivers. Factors such as automated mode duration, traffic density, and Non-Driving-Related Tasks were assessed. Results reveal significant impacts on takeover perception, identifying three driver profiles: averse, adaptive, and confident, crucial for vehicle acceptance.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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