Next Stop: Passenger Perspectives on Autonomous Trains

Andrea Arzer*, Lauren Beehler*, Marloes Vredenborg

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

While extensive research exists on autonomous cars for private use, there is a notable gap in understanding public opinions on autonomous trains. Understanding passengers’ views on a technology that might be available to them in the next decade could highly influence its success. This paper researches factors influencing potential passengers when deciding to ride fully autonomous trains and explores solutions to counteract negative perceptions. To complement the available research on this topic that has been conducted using quantitative methods, this paper describes a multi-method qualitative study combining focus groups and creative problem-solving sessions. Key findings include participants’ distrust in unfamiliar systems and hesitation about the absence of human staff onboard. Proposed ideas include the visible implementation of additional safety features available to the passengers, the adaptation of the train interior to make it more inviting, and the provision of information about the operation of the autonomous trains. This study uncovered different perspectives and concerns related to autonomous railway vehicles, along with solutions that can be implemented to increase passenger trust. However, it also emphasizes the complexity of the topic, illustrating the necessity for additional research.
Original languageEnglish
Title of host publicationHCI in Mobility, Transport, and Automotive Systems - 6th International Conference, MobiTAS 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
Subtitle of host publicationHCI in Mobility, Transport, and Automotive Systems
EditorsHeidi Krömker
PublisherSpringer
Pages3-25
Number of pages23
ISBN (Electronic)978-3-031-60480-5
ISBN (Print)978-3-031-60479-9
DOIs
Publication statusPublished - 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14733 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

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