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Rethinking the road ahead – generation Z’s perspectives on AI-based mobility services

Miskolczi, Márk ORCID: https://orcid.org/0000-0002-4779-2952, Kökény, László ORCID: https://orcid.org/0000-0001-5375-4082 and Jászberényi, Melinda ORCID: https://orcid.org/0000-0002-7839-5036 (2025) Rethinking the road ahead – generation Z’s perspectives on AI-based mobility services. Transportation Research Interdisciplinary Perspectives, 31 . DOI 10.1016/j.trip.2025.101475

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Official URL: https://doi.org/10.1016/j.trip.2025.101475


Abstract

Empirical studies project that autonomous vehicles (AVs) with SAE Levels 4/5 will become widely available for passenger transport by the early 2030s. However, consumer expectations and perceived risks related to this technology remain insufficiently understood. This study addresses this gap by exploring how Generation Z – arguably the most receptive segment to Industry 4.0 innovations – perceives highly automated vehicles. Focus group interviews (n discussions =5, n subject =25) were conducted and analysed following the three-stage Grounded Theory method developed by Corbin – Strauss (1990). The resulting conceptual model – TRACE (Technology- related Repertoires of Attitudes, Control, and Engagement) – identifies critical yet under-researched factors such as alternative vehicle usage patterns, AI-scepticism, and shifting human–machine (AI) interdependence that may significantly shape AV acceptance. This research offers a theoretical contribution to the field of human–technology interaction and practical insights for stakeholders aiming to accelerate the socially responsible diffusion of AVs.

Item Type:Article
Uncontrolled Keywords:highly automated (SAE Level 4–5) autonomous vehicles ; Generation Z ; Artificial intelligence ; Machine-human interdependence ; Driving experience
Divisions:Institute of Sustainable Development
Subjects:Information economy
Media and communication
Funders:National Research, Development and Innovation Office
Projects:147547
DOI:10.1016/j.trip.2025.101475
ID Code:11274
Deposited By: MTMT SWORD
Deposited On:28 May 2025 08:29
Last Modified:28 May 2025 08:29

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