Development and validation of the Automated Vehicle Acceptance Questionnaire for Pedestrians (AVAQ-P)

• Acceptance of automated vehicles by pedestrians is little understood; • Study proposes and validates questionnaire for assessment of automated vehicle acceptance (AVA) by pedestrians; • Stringent three-step approach was adopted for questionnaire validation; • Clear, valid and reliable seven-factor structure emerged; • Future research should replicate study with larger, more representative and gender-diverse population of pedestrians. The investigation of automated vehicle acceptance (AVA) has received considerable attention in the past few years. Understanding the factors impacting their acceptance is pivotal to ensure a large-scale and wide acceptance of AVs. The AVA by pedestrians is still little understood. To address this knowledge gap, the main objective of this study is to develop and validate an instrument for the assessment of AVA by pedestrians. We tested this instrument on a German sample of pedestrians ( n = 136), considering their individual demographic characteristics, and level of affinity for technology interaction. A four-step approach was adopted to analyze the data. First, a principal component analysis was performed to reduce the number of items, exploring the sources of variation in the dataset. Second, the principal components were subjected to a confirmatory factor analysis to investigate the validity and reliability of the proposed measurement model. Third, structural equation modeling was conducted to estimate the path relationships between our constructs. The study has revealed differences between the effect sizes and significance levels of the factors influencing pedestrians’ AVA. The AVA by pedestrians was most strongly influenced by affinity for technology interaction (i.e., extent to which the individual actively approaches or avoids the interaction with new systems), performance expectancy (i.e., extent to which the individual believes that using the system will support them in achieving gains in the performance of the task) and social influence (i.e., extent to which the individual believes that people important to them think that the individual should perform the behavior). Male pedestrians were more likely to accept AVs. We also revealed significant interaction effects of age on the variables in our model. With this work, we have contributed to the development and validation of the Automated Vehicle Acceptance Questionnaire for Pedestrians (AVAQ-P). We recommend future research to replicate the study with a larger, more representative and gender-diverse population of pedestrians, considering cross-cultural differences in AVA.

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Publication Details

Journal
Transportation Research Part F Traffic Psychology and Behaviour
Published
2025-05-14
DOI
https://doi.org/10.1016/j.trf.2025.04.016
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
2.44
Controls
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article

Development and validation of the Automated Vehicle Acceptance Questionnaire for Pedestrians (AVAQ-P)

Marc Wilbrink, Michael Oehl, Sina Nordhoff, Marjan Hagenzieker
1 citations
Transportation Research Part F Traffic Psychology and Behaviour
Human-Automation Interaction and Safety
2.44
article

Development and validation of the Automated Vehicle Acceptance Questionnaire for Pedestrians (AVAQ-P)

Marc Wilbrink, Michael Oehl, Sina Nordhoff, Marjan Hagenzieker
article en
1 citations

Abstract

• Acceptance of automated vehicles by pedestrians is little understood; • Study proposes and validates questionnaire for assessment of automated vehicle acceptance (AVA) by pedestrians; • Stringent three-step approach was adopted for questionnaire validation; • Clear, valid and reliable seven-factor structure emerged; • Future research should replicate study with larger, more representative and gender-diverse population of pedestrians. The investigation of automated vehicle acceptance (AVA) has received considerable attention in the past few years. Understanding the factors impacting their acceptance is pivotal to ensure a large-scale and wide acceptance of AVs. The AVA by pedestrians is still little understood. To address this knowledge gap, the main objective of this study is to develop and validate an instrument for the assessment of AVA by pedestrians. We tested this instrument on a German sample of pedestrians ( n = 136), considering their individual demographic characteristics, and level of affinity for technology interaction. A four-step approach was adopted to analyze the data. First, a principal component analysis was performed to reduce the number of items, exploring the sources of variation in the dataset. Second, the principal components were subjected to a confirmatory factor analysis to investigate the validity and reliability of the proposed measurement model. Third, structural equation modeling was conducted to estimate the path relationships between our constructs. The study has revealed differences between the effect sizes and significance levels of the factors influencing pedestrians’ AVA. The AVA by pedestrians was most strongly influenced by affinity for technology interaction (i.e., extent to which the individual actively approaches or avoids the interaction with new systems), performance expectancy (i.e., extent to which the individual believes that using the system will support them in achieving gains in the performance of the task) and social influence (i.e., extent to which the individual believes that people important to them think that the individual should perform the behavior). Male pedestrians were more likely to accept AVs. We also revealed significant interaction effects of age on the variables in our model. With this work, we have contributed to the development and validation of the Automated Vehicle Acceptance Questionnaire for Pedestrians (AVAQ-P). We recommend future research to replicate the study with a larger, more representative and gender-diverse population of pedestrians, considering cross-cultural differences in AVA.

Transportation Research Part F Traffic Psychology and BehaviourVol. 113
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), University of California, Davis (US), Delft University of Technology (NL)
Openalex Percentile: Top 13%
Human-Automation Interaction and Safety
2.44
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