Passenger Immersive Experiences in Autonomous Vehicles: A Comprehensive Review and Proposed Framework

Research output: Journal PublicationReview articlepeer-review

Abstract

This study investigates key factors influencing the immersive experience of passengers in autonomous vehicles (AVs) and proposes a novel theoretical model. In this model, four core dimensions were identified: (1) Emotional and Sensory Experience, (2) Interaction and Engagement Experience, (3) Trust and Safety Experience and (4) Dispositional Experience. It is found that Emotional and Sensory factors, such as lighting and sound, primarily affect passenger comfort and mood. In contrast, the Interaction and Engagement factors that focus on human–machine interaction (HMI) and AR/VR devices enhance passengers’ engagement. As for trust and safety factors, passengers’ confidence towards AVs is addressed through clear communication during driving processes. Dispositional factors, including technology acceptance and personalisation, contribute to passengers’ overall satisfaction in AVs. In addition, external factors such as intelligent transportation systems (ITSs), intelligent connected vehicles (ICVs) and smart city infrastructure further impact passengers’ experiences in safety and efficiency. The study highlights several emerging research areas requiring further investigation, such as multisensory feedback, dynamic personalisation and cultural inclusivity differences in AV experience. The proposed theoretical model serves as a foundation for future work aimed at enabling the design of AV systems that are more attentive and accommodating to passengers by sourcing control both domestically and externally, ultimately enhancing the passengers’ experience.

Original languageEnglish
Article number4874071
JournalJournal of Advanced Transportation
Volume2025
Issue number1
DOIs
Publication statusPublished - 2025

Keywords

  • autonomous vehicles (AVs)
  • design
  • multisensory
  • passenger immersive experience

ASJC Scopus subject areas

  • Automotive Engineering
  • Economics and Econometrics
  • Mechanical Engineering
  • Computer Science Applications
  • Strategy and Management

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