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Human-Centered Approaches to Automated Vehicles

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

Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 3306

Special Issue Editors


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Guest Editor
TECNALIA, Basque Research and Technology Alliance, 48160 Derio, Spain
Interests: automated driving; shared control; human–vehicle cooperation; vehicle dynamics; fail-operational strategies

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Guest Editor
TECNALIA, Basque Research and Technology Alliance, 48160 Derio, Spain
Interests: automated driving; shared control; human–vehicle cooperation; optimal control

E-Mail Website
Guest Editor
Department of Automatic Control and Systems Engineering, University of the Basque Country (UPV/EHU), 48013 Bilbao, Spain
Interests: model based predictive control; virtual sensors; bioengineering; robotics; automated driving

E-Mail Website
Guest Editor
TECNALIA, Basque Research and Technology Alliance, 48160 Derio, Spain
Interests: automated driving; shared control; vehicle dynamics

Special Issue Information

Dear Colleagues,

This Special Issue will explore how people and automated vehicles (AVs) will work together as technology continues to change quickly. Vehicles are becoming more focused on people and their needs; thus, it is important to study innovative human-centered approaches in shaping different mobility solutions. Special attention will be paid to how humans and machines communicate and collaborate with each other in cars and how researchers are working to make sure that technology helps people stay in control when they are driving. Novel ADAS adapting to human needs and in-cabin monitoring tools are a good example of such technologies. This Special Issue will also provide insights into what could happen with the implementation of vehicles with high levels of automation, stressing how important it is to mix technology with features that people need for safety and comfort. In this sense, the whole human–vehicle collaboration spectrum will be addressed, not only considering drivers but also passengers, teleoperators, and interactions between the vehicle and other road users.

Dr. Sergio E. Diaz-Briceno
Dr. Mauricio Marcano
Dr. Asier Zubizarreta
Dr. Joshué Pérez Rastelli
Guest Editors

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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • advanced driver assistance systems
  • shared control
  • traded control
  • human–machine interfaces (HMIs)
  • external HMIs
  • teleoperation
  • in-cabin monitoring systems
  • gesture control
  • explainable AI towards AV users
  • human-centered methodologies in AVs

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Published Papers (2 papers)

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Research

24 pages, 2268 KiB  
Article
Fusion of Driving Behavior and Monitoring System in Scenarios of Driving Under the Influence: An Experimental Approach
by Jan-Philipp Göbel, Niklas Peuckmann, Thomas Kundinger and Andreas Riener
Appl. Sci. 2025, 15(10), 5302; https://doi.org/10.3390/app15105302 - 9 May 2025
Viewed by 192
Abstract
Driving under the influence of alcohol (DUI) remains a leading cause of accidents globally, with accident risk rising exponentially with blood alcohol concentration (BAC). This study aims to distinguish between sober and intoxicated drivers using driving behavior analysis and driver monitoring system (DMS), [...] Read more.
Driving under the influence of alcohol (DUI) remains a leading cause of accidents globally, with accident risk rising exponentially with blood alcohol concentration (BAC). This study aims to distinguish between sober and intoxicated drivers using driving behavior analysis and driver monitoring system (DMS), technologies that align with emerging EU regulations. In a driving simulator, twenty-three participants (average age: 32) completed five drives (one practice and two each while sober and intoxicated) on separate days across city, rural, and highway settings. Each 30-minute drive was analyzed using eye-tracking and driving behavior data. We applied significance testing and classification models to assess the data. Our study goes beyond the state of the art by a) combining data from various sensors and b) not only examining the effects of alcohol on driving behavior but also using these data to classify driver impairment. Fusing gaze and driving behavior data improved classification accuracy, with models achieving over 70% accuracy in city and rural conditions and a Long Short-Term Memory (LSTM) network reaching up to 80% on rural roads. Although the detection rate is, of course, still far too low for a productive system, the results nevertheless provide valuable insights for improving DUI detection technologies and enhancing road safety. Full article
(This article belongs to the Special Issue Human-Centered Approaches to Automated Vehicles)
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22 pages, 3526 KiB  
Article
Towards Enhanced Autonomous Driving Takeovers: Fuzzy Logic Perspective for Predicting Situational Awareness
by Goran Ferenc, Dragoje Timotijević, Ivana Tanasijević and Danijela Simić
Appl. Sci. 2024, 14(13), 5697; https://doi.org/10.3390/app14135697 - 29 Jun 2024
Cited by 4 | Viewed by 2528
Abstract
This paper investigates the application of fuzzy logic to enhance situational awareness in Advanced Driver Assistance Systems (ADAS). Situational awareness is critical for drivers to respond appropriately to dynamic driving scenarios. As car automation increases, monitoring situational awareness ensures that drivers can effectively [...] Read more.
This paper investigates the application of fuzzy logic to enhance situational awareness in Advanced Driver Assistance Systems (ADAS). Situational awareness is critical for drivers to respond appropriately to dynamic driving scenarios. As car automation increases, monitoring situational awareness ensures that drivers can effectively take control of the vehicle when needed. Our study explores whether fuzzy logic can accurately assess situational awareness using a set of 14 critical predictors categorized into time decision, criticality, eye-related metrics, and driver experience. We based our work on prior research that used machine learning (ML) models to achieve high accuracy. Our proposed fuzzy logic system aims to match the predictive accuracy of ML models while providing additional benefits in terms of interpretability and robustness. This approach emphasizes a fresh perspective on situational awareness within ADAS, potentially improving safety and efficiency in real-world driving scenarios. Full article
(This article belongs to the Special Issue Human-Centered Approaches to Automated Vehicles)
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