Acceptability of automated vehicles in Portugal: profiling prospective users

• Type: Chapter or Part of a Book
• Date: 2026

Authors

António Lobo (Author) FEUP; Sérgio Pedro Duarte (Author) FEUP; Daniela Monteiro (Author) Other; Daniel Silva (Author) FPCEUP; Sara Ferreira (Author) FEUP; Liliana Cunha (Author) FPCEUP

Book

Title: Transport Transitions: Advancing Sustainable and Inclusive Mobility. TRAconference 2024

Pages: 497-501

ISBN: 978-3-032-06762-3

Electronic ISBN: 978-3-032-06763-0

Indexing

Scopus

Associated Projects

AUTODRIVING - Autodriving - Modelação do comportamento do condutor em contexto de veículo autónomo com recurso ao simulador de condução

Other information

DOI: 10.1007/978-3-032-06763-0_71

Abstract (EN): The continuous development of advanced driver assistance systems is paving the way for the deployment of autonomous vehicles. Until then, manual vehicles and partially automated vehicles (AVs) will co-exist. Past experience has shown that the deployment of new technology must consider users’ acceptability and adoption. This is the case of AVs, that must provide safety and comfortable travel experiences. To evaluate acceptability profiles towards AVs, this study analyses the determinant factors of AVs acceptability to identify different Portuguese population clusters. A questionnaire was developed to explore prospective users’ representations regarding benefits and expectations, risks and concerns, previous experience with automated driving technology, and preferred use cases for AVs. A cluster analysis was performed using the k-means algorithm and, after, chi-square tests characterized cluster membership. In the end, acceptability profiles were compared for different use cases using ANOVA post-hoc tests. Three clusters of prospective users were identified: objectors, ambivalents, and enthusiasts. Driving pleasure, safety, reliability of the technology, and data privacy are prevailing negative factors while improved road safety, reduced emissions, and non-driving tasks possibilities favor acceptability. Sociodemographic characteristics, like income, education, place of residence, and self-perception about the adoption of new technologies reflected the main differences between clusters.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4