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Applied Sciences
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Autonomous Vehicles: Advances and Prospects
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Autonomous Vehicles: Advances and Prospects

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 1119

Special Issue Editor

Dr. Erika E. Gallegos

E-Mail Website
Guest Editor
Department of Systems Engineering, Colorado State University, 6029 Campus Delivery, Fort Collins, CO 80523, USA
Interests: connected vehicles; connected infrastructure; autonomous vehicles

Special Issue Information

Dear Colleagues,

This Special Issue of Applied Sciences aims to highlight the latest innovations, methodologies, and applications in the field of autonomous vehicles (AVs). We welcome original research articles, case studies, and comprehensive reviews covering a wide spectrum of topics including, but not limited to, the following: artificial intelligence and machine learning for autonomy, sensor fusion, safety and validation techniques, reliability, human–machine interaction, cybersecurity, infrastructure integration, vehicle connectivity and V2X communication, perception systems, path planning, control algorithms, and regulatory frameworks. We also encourage submissions that address societal impacts, mobility efficiency, and the integration of AVs into personal, commercial, and public transport systems.

As autonomous vehicle technology continues to evolve, your expertise and research can play a vital role in shaping the future of transportation. We welcome submissions that highlight cutting-edge innovations, theoretical developments, and real-world implementations. We look forward to your valuable contributions and to sharing the latest advancements with the broader scientific and engineering community.

Dr. Erika E. Gallegos
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • autonomous vehicles
  • automated vehicles
  • connected vehicles
  • artificial intelligence
  • computer vision
  • human–machine interaction
  • intelligent transportation systems
  • safety
  • cybersecurity
  • human factors

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Published Papers (2 papers)

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Research

19 pages, 20107 KB  
Article
Visualizing Driving Maneuvers Through Peripheral Displays: A Comparative Study of iHMI Design in Autonomous Vehicles
by Leonhard Rottmann, Anastasia Stang, Aniella Johannsen, Mathias Niedling and Mark Vollrath
Appl. Sci. 2025, 15(22), 12044; https://doi.org/10.3390/app152212044 - 12 Nov 2025
Viewed by 338
Abstract
Autonomous driving is anticipated to increase safety, efficiency, and accessibility of passenger transportation. Passengers are given freedom in the use of travel time through the potential to conduct non-driving related tasks (NDRTs). However, factors such as trust and motion sickness pose challenges to [...] Read more.
Autonomous driving is anticipated to increase safety, efficiency, and accessibility of passenger transportation. Passengers are given freedom in the use of travel time through the potential to conduct non-driving related tasks (NDRTs). However, factors such as trust and motion sickness pose challenges to the widespread adoption of this technology. Human–machine interfaces (HMIs) have shown potential in mitigating motion sickness and fostering trust calibration in autonomous vehicles (AVs), e.g., by visualizing upcoming or current maneuvers of the vehicle. The majority of research on such HMIs relies on the passengers’ attention, preventing uninterrupted NDRT execution and thus impeding the automation’s usefulness. In this paper, we present a visual HMI, providing AV passengers with information about current driving maneuvers through their peripheral fields of view. This method of information transmission is compared to conventional in-vehicle displays and LED strips regarding perceptibility and distraction. In a controlled laboratory setting, N = 34 participants experienced each HMI condition, indicating their perception of the maneuver visualizations using joystick input while either focusing on a fixation cross to measure perceptibility or solving math tasks to measure distraction. The peripheral HMIs caused better maneuver perception (ηp2=0.12) and lower distraction (ηg2=0.16) from a visual NDRT than the conventional displays. These results yield implications for the design of HMIs for motion sickness mitigation and trust calibration in AVs. Full article
(This article belongs to the Special Issue Autonomous Vehicles: Advances and Prospects)
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23 pages, 11803 KB  
Article
Rearward Seating Orientation Decreases Trust and Increases Motion Sickness in Autonomous Vehicles
by Leonhard Rottmann, Alina Waldmann, Aniella Johannsen and Mark Vollrath
Appl. Sci. 2025, 15(22), 12027; https://doi.org/10.3390/app152212027 - 12 Nov 2025
Viewed by 576
Abstract
As the development of autonomous vehicles (AVs) progresses, new seating arrangements are emerging. Face-to-face seating is common in SAE L4 AV concepts and is intended to facilitate social interaction during autonomous driving, enabling previously unfeasible non-driving related tasks (NDRTs). However, this is countered [...] Read more.
As the development of autonomous vehicles (AVs) progresses, new seating arrangements are emerging. Face-to-face seating is common in SAE L4 AV concepts and is intended to facilitate social interaction during autonomous driving, enabling previously unfeasible non-driving related tasks (NDRTs). However, this is countered by the unpopularity of rearward seating orientations, which is particularly pronounced in cars. In order to develop countermeasures to address this unpopularity, a deeper understanding of the underlying mechanisms is required. This study validates a model that predicts the acceptance of AVs and takes seating orientation into account. To this end, a study with N = 46 participants was conducted to investigate the influence of seating orientation on AV acceptance and related factors such as transparency, trust, and motion sickness. Additionally, internal human–machine interfaces (iHMIs) were evaluated in regard to their ability to compensate for the disadvantages of a rearward seating orientation. To achieve a realistic implementation of a fully functional SAE L4 AV, an experimental vehicle was equipped with a steering and pedal robot, performing self-driven journeys on a test track. The iHMIs provided information about upcoming maneuvers and detected road users. While engaged in a social NDRT, participants experienced a total of six journeys. Seating orientation and iHMI visualization were manipulated between journeys. Rearward-facing passengers showed lower levels of trust and higher levels of motion sickness than forward-facing passengers. However, the iHMIs had no effect on acceptance or related factors. Based on these findings, an updated version of the model is proposed, showing that rearward-facing passengers in autonomous vehicles pose a particular challenge for trust calibration and motion sickness mitigation. During NDRTs, iHMIs which depend on the attention of AV occupants for information transfer appear to be ineffective. Implications for future research and design of iHMIs to address this challenge are discussed. Full article
(This article belongs to the Special Issue Autonomous Vehicles: Advances and Prospects)
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