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Automotive User Interfaces and Interactions in Automated Driving
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Automotive User Interfaces and Interactions in Automated Driving

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (15 December 2019) | Viewed by 42275

Special Issue Editors

Dr. Gerrit Meixner

E-Mail Website
Guest Editor
Usability and Interaction Technology Laboratory (UniTyLab), Heilbronn University, 74081 Heilbronn, Germany
Interests: human-computer interaction; usability engineering; interaction technologies; mixed reality
Special Issues, Collections and Topics in MDPI journals
Dr. Ignacio Alvarez

E-Mail Website
Guest Editor
Autonomous Driving Research, Intel Labs, Intel Corporation, Beaverton, OR 97007, USA
Interests: automated driving; intelligent transportation; vehicle safety; connected vehicles; Artificial Intelligence; user experience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This special issue journal is about automotive user interfaces. In the last years, the importance of user interfaces for in-vehicle usage has increased strongly. Different studies show that over 80% of today’s innovations in the automotive industry are based on car electronics and its software. These innovations can be categorized into hidden technologies (e.g., ASP, ESP), comfort functions (e.g., navigation, communication, entertainment) or driver assistance (e.g., distance checking). Especially the last two categories have to be configurable by the driver and therefore require a certain amount of driver interaction. This results in a need for a modern and consistent automotive user interface which on one hand allows the configuration of these systems but which on the other hand conforms to the specialized requirements of the automotive industry. Some of these requirements are: the interaction devices have to be integrated into a limited space; the automotive user interface has to be intuitively usable and adaptable, since drivers generally do not get an extensive explanation and the automotive user interface has to be very easy to use and should distract the driver as little as possible from his main task of driving. The increased complexity of automotive user interfaces, the importance of using consumer electronic devices like e.g. smartphones in the car as well as autonomous driving and e-vehicles has induced a lot of research at universities and industrial companies.

Therefore, we would like to gather your new research in a special issue journal to bring together the leading researchers and practitioners in the field of automotive user interfaces from the traditional field of automotive OEMs and suppliers as well as from modern IT companies.

Prof. Gerrit Meixner
Dr. Ignacio Alvarez
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. Information is an international peer-reviewed open access monthly 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 1600 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

  • Automotive User Interface
  • Human-Computer-Interaction
  • Multi-modal, speech, audio, gestural, natural input/output
  • Autonomous and Electric vehicle interfaces
  • Driver performance / driver behavior
  • Interactions with semi and fully-automated vehicles
  • Human-Vehicle cooperation in (partially) automated vehicles
  • Impact of human-machine interfaces on driver situation awareness
  • Vehicle occupant monitoring systems
  • Effect of exterior human-machine interfaces on road users’ behavior
  • Adaptive / Learning vehicle assistance systems
  • Trust in Automation
  • Perceptions of Safety in Automated Driving

Related Special Issue

Published Papers (6 papers)

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Research

19 pages, 4106 KiB  
Article
The Effects of a Predictive HMI and Different Transition Frequencies on Acceptance, Workload, Usability, and Gaze Behavior during Urban Automated Driving
by Tobias Hecht, Stefan Kratzert and Klaus Bengler
Information 2020, 11(2), 73; https://doi.org/10.3390/info11020073 - 30 Jan 2020
Cited by 18 | Viewed by 4248
Abstract
Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and time-critical take-over situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more [...] Read more.
Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and time-critical take-over situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more attention and the ability to engage in non-driving related activities (NDRA) starting from SAE Level 3 automation poses new questions to HMI design. Moreover, future introduction scenarios and automated capabilities are still unclear. Thus, we designed, executed, and assessed a driving simulator study focusing on the effect of different transition frequencies and a predictive HMI while freely engaging in naturalistic NDRA. In the study with 33 participants, we found transition frequency to have effects on workload and acceptance, as well as a small impact on the usability evaluation of the system. Trust, however, was not affected. The predictive HMI was used and accepted, as can be seen by eye-tracking data and the post-study questionnaire, but could not mitigate the above-mentioned negative effects induced by transition frequency. Most attractive activities were window gazing, chatting, phone use, and reading magazines. Descriptively, window gazing and chatting gained attractiveness when interrupted more often, while reading magazines and playing games were negatively affected by transition rate. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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17 pages, 14141 KiB  
Article
Information Needs and Visual Attention during Urban, Highly Automated Driving—An Investigation of Potential Influencing Factors
by Alexander Feierle, Simon Danner, Sarah Steininger and Klaus Bengler
Information 2020, 11(2), 62; https://doi.org/10.3390/info11020062 - 25 Jan 2020
Cited by 23 | Viewed by 3810
Abstract
During highly automated driving, the passenger is allowed to conduct non-driving related activities (NDRA) and no longer has to act as a fallback at the functional limits of the driving automation system. Previous research has shown that at lower levels of automation, passengers [...] Read more.
During highly automated driving, the passenger is allowed to conduct non-driving related activities (NDRA) and no longer has to act as a fallback at the functional limits of the driving automation system. Previous research has shown that at lower levels of automation, passengers still wish to be informed about automated vehicle behavior to a certain extent. Due to the aim of the introduction of urban automated driving, which is characterized by high complexity, we investigated the information needs and visual attention of the passenger during urban, highly automated driving. Additionally, there was an investigation into the influence of the experience of automated driving and of NDRAs on these results. Forty participants took part in a driving simulator study. As well as the information presented on the human–machine interface (system status, navigation information, speed and speed limit), participants requested information about maneuvers, reasons for maneuvers, environmental settings and additional navigation data. Visual attention was significantly affected by the NDRA, while the experience of automated driving had no effect. Experience and NDRA showed no significant effect on the need for information. Differences in information needs seem to be due to the requirements of the individual passenger, rather than the investigated factors. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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17 pages, 1583 KiB  
Article
From HMI to HMIs: Towards an HMI Framework for Automated Driving
by Klaus Bengler, Michael Rettenmaier, Nicole Fritz and Alexander Feierle
Information 2020, 11(2), 61; https://doi.org/10.3390/info11020061 - 25 Jan 2020
Cited by 112 | Viewed by 11754
Abstract
During automated driving, there is a need for interaction between the automated vehicle (AV) and the passengers inside the vehicle and between the AV and the surrounding road users outside of the car. For this purpose, different types of human machine interfaces (HMIs) [...] Read more.
During automated driving, there is a need for interaction between the automated vehicle (AV) and the passengers inside the vehicle and between the AV and the surrounding road users outside of the car. For this purpose, different types of human machine interfaces (HMIs) are implemented. This paper introduces an HMI framework and describes the different HMI types and the factors influencing their selection and content. The relationship between these HMI types and their influencing factors is also presented in the framework. Moreover, the interrelations of the HMI types are analyzed. Furthermore, we describe how the framework can be used in academia and industry to coordinate research and development activities. With the help of the HMI framework, we identify research gaps in the field of HMI for automated driving to be explored in the future. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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19 pages, 1447 KiB  
Article
Does Information on Automated Driving Functions and the Way of Presenting It before Activation Influence Users’ Behavior and Perception of the System?
by Simon Danner, Matthias Pfromm and Klaus Bengler
Information 2020, 11(1), 54; https://doi.org/10.3390/info11010054 - 18 Jan 2020
Cited by 10 | Viewed by 3318
Abstract
Information on automated driving functions when automation is not activated but is available have not been investigated thus far. As the possibility of conducting non-driving related activities (NDRAs) is one of the most important aspects when it comes to perceived usefulness of automated [...] Read more.
Information on automated driving functions when automation is not activated but is available have not been investigated thus far. As the possibility of conducting non-driving related activities (NDRAs) is one of the most important aspects when it comes to perceived usefulness of automated cars and many NDRAs are time-dependent, users should know the period for which automation is available, even when not activated. This article presents a study (N = 33) investigating the effects of displaying the availability duration before—versus after—activation of the automation on users’ activation behavior and on how the system is rated. Furthermore, the way of addressing users regarding the availability on a more personal level to establish “sympathy” with the system was examined with regard to acceptance, usability, and workload. Results show that displaying the availability duration before activating the automation reduces the frequency of activations when no NDRA is executable within the automated drive. Moreover, acceptance and usability were higher and workload was reduced as a result of this information being provided. No effects were found with regard to how the user was addressed. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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20 pages, 1837 KiB  
Article
Driving Style: How Should an Automated Vehicle Behave?
by Luis Oliveira, Karl Proctor, Christopher G. Burns and Stewart Birrell
Information 2019, 10(6), 219; https://doi.org/10.3390/info10060219 - 25 Jun 2019
Cited by 56 | Viewed by 10706
Abstract
This article reports on a study to investigate how the driving behaviour of autonomous vehicles influences trust and acceptance. Two different designs were presented to two groups of participants (n = 22/21), using actual autonomously driving vehicles. The first was a vehicle [...] Read more.
This article reports on a study to investigate how the driving behaviour of autonomous vehicles influences trust and acceptance. Two different designs were presented to two groups of participants (n = 22/21), using actual autonomously driving vehicles. The first was a vehicle programmed to drive similarly to a human, “peeking” when approaching road junctions as if it was looking before proceeding. The second design had a vehicle programmed to convey the impression that it was communicating with other vehicles and infrastructure and “knew” if the junction was clear so could proceed without ever stopping or slowing down. Results showed non-significant differences in trust between the two vehicle behaviours. However, there were significant increases in trust scores overall for both designs as the trials progressed. Post-interaction interviews indicated that there were pros and cons for both driving styles, and participants suggested which aspects of the driving styles could be improved. This paper presents user information recommendations for the design and programming of driving systems for autonomous vehicles, with the aim of improving their users’ trust and acceptance. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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22 pages, 2422 KiB  
Article
User Education in Automated Driving: Owner’s Manual and Interactive Tutorial Support Mental Model Formation and Human-Automation Interaction
by Yannick Forster, Sebastian Hergeth, Frederik Naujoks, Josef Krems and Andreas Keinath
Information 2019, 10(4), 143; https://doi.org/10.3390/info10040143 - 17 Apr 2019
Cited by 50 | Viewed by 7185
Abstract
Automated driving systems (ADS) and a combination of these with advanced driver assistance systems (ADAS) will soon be available to a large consumer population. Apart from testing automated driving features and human–machine interfaces (HMI), the development and evaluation of training for interacting with [...] Read more.
Automated driving systems (ADS) and a combination of these with advanced driver assistance systems (ADAS) will soon be available to a large consumer population. Apart from testing automated driving features and human–machine interfaces (HMI), the development and evaluation of training for interacting with driving automation has been largely neglected. The present work outlines the conceptual development of two possible approaches of user education which are the owner’s manual and an interactive tutorial. These approaches are investigated by comparing them to a baseline consisting of generic information about the system function. Using a between-subjects design, N = 24 participants complete one training prior to interacting with the ADS HMI in a driving simulator. Results show that both the owner’s manual and an interactive tutorial led to an increased understanding of driving automation systems as well as an increased interaction performance. This work contributes to method development for the evaluation of ADS by proposing two alternative approaches of user education and their implications for both application in realistic settings and HMI testing. Full article
(This article belongs to the Special Issue Automotive User Interfaces and Interactions in Automated Driving)
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