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Machines
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Human–Machine Interaction for Autonomous Vehicles
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Human–Machine Interaction for Autonomous Vehicles

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: closed (30 October 2023) | Viewed by 5527

Special Issue Editor

Dr. Angelica Reyes

E-Mail Website
Guest Editor
Castelldefels School of Telecommunications and Aerospace Engineering, Edificio C4, Despacho 011, Esteve Terradas, 7, Castelldefels 08860, Barcelona, Spain
Interests: data science; human–computer interaction; autonomous vehicles; artificial intelligence

Special Issue Information

Dear Colleagues,

Today's advances in artificial intelligence are rapidly approaching the inflection point at which autonomous vehicles (AVs), both on land and in the air, will be a daily life reality.

AVs are systems that consist of software, hardware, humans, and their interactions. This Special Issue entails the problem of understanding and shaping how autonomous vehicles interact with humans as an active part of the whole transportation environment.

We invite researchers to contribute to human–machine interface design, communication with vulnerable road users, prediction of human behaviour, emotion recognition, and AI systems that grasp the myriad ways that people interact with their vehicles, among others.

This Special Issue welcomes all forms of human–machine interaction for autonomous vehicle proposals: research contributions, proof of concept, state-of-the-art, reviews, etc.

Dr. Angelica Reyes
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 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. Machines 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 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
  • human factors
  • human–machine interaction

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Published Papers (2 papers)

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Research

21 pages, 4748 KiB  
Article
Assistive Self-Driving Car Networks to Provide Safe Road Ecosystems for Disabled Road Users
by Juan Guerrero-Ibañez, Juan Contreras-Castillo, Ismael Amezcua-Valdovinos and Angelica Reyes-Muñoz
Machines 2023, 11(10), 967; https://doi.org/10.3390/machines11100967 - 17 Oct 2023
Cited by 1 | Viewed by 2351
Abstract
Disabled pedestrians are among the most vulnerable groups in road traffic. Using technology to assist this vulnerable group could be instrumental in reducing the mobility challenges they face daily. On the one hand, the automotive industry is focusing its efforts on car automation. [...] Read more.
Disabled pedestrians are among the most vulnerable groups in road traffic. Using technology to assist this vulnerable group could be instrumental in reducing the mobility challenges they face daily. On the one hand, the automotive industry is focusing its efforts on car automation. On the other hand, in recent years, assistive technology has been promoted as a tool for consolidating the functional independence of people with disabilities. However, the success of these technologies depends on how well they help self-driving cars interact with disabled pedestrians. This paper proposes an architecture to facilitate interaction between disabled pedestrians and self-driving cars based on deep learning and 802.11p wireless technology. Through the application of assistive technology, we can locate the pedestrian with a disability within the road traffic ecosystem, and we define a set of functionalities for the identification of hand gestures of people with disabilities. These functions enable pedestrians with disabilities to express their intentions, improving their confidence and safety level in tasks within the road ecosystem, such as crossing the street. Full article
(This article belongs to the Special Issue Human–Machine Interaction for Autonomous Vehicles)
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19 pages, 2120 KiB  
Article
Human–Machine Shared Steering Control for Vehicle Lane Changing Using Adaptive Game Strategy
by Xiaodong Wu, Chengrui Su and Liang Yan
Machines 2023, 11(8), 838; https://doi.org/10.3390/machines11080838 - 17 Aug 2023
Cited by 3 | Viewed by 2122
Abstract
Human–machine shared control of intelligent vehicles is considered an important technology during the industrial application of autonomous driving systems. Among the engineering practices in driver assistance systems, shared steering control is one of the important applications for the human–machine interaction. However, how to [...] Read more.
Human–machine shared control of intelligent vehicles is considered an important technology during the industrial application of autonomous driving systems. Among the engineering practices in driver assistance systems, shared steering control is one of the important applications for the human–machine interaction. However, how to deal with human–machine conflicts during emergency scenarios is the main challenge for the controller’s design. Most shared control approaches usually generate machine-oriented results without enough attention to the driver’s reaction. By taking the human driver and machine system as two intelligent agents, this paper proposes a game-based control scheme to achieve a dynamic authority allocation during the lane changing maneuver. Based on the modeling of predicted trajectories of the human driver, a human-intention-based shared steering control is designed to achieve dynamic Nash game equilibrium. Moreover, a human-oriented shared steering mechanism is employed to not only benefit from automated machine assistance, but also make full play of human contributions. Using quantitative comparative analysis in lane changing scenarios with different human–machine conflicts, a better performance by considering both driving comfort and safety is achieved. Full article
(This article belongs to the Special Issue Human–Machine Interaction for Autonomous Vehicles)
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