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Human-Computer Interaction: Advances, Challenges and Opportunities

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 1228

Special Issue Editor


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Guest Editor
Division of Interdisciplinary Studies in Cultural Intelligence (HCI Science Major), Dongduk Women’s University, Seoul 02748, Republic of Korea
Interests: human-computer interaction

Special Issue Information

Dear Colleagues,

Human–computer interaction (HCI) is undergoing significant transformation as technologies such as artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and the Internet of Things (IoT) are increasingly integrated into various domains. These advancements are reshaping the ways users interact with digital systems, presenting new opportunities to enhance user experience, increase system functionality, and improve interaction design across platforms.

This Special Issue on "Human-Computer Interaction: Advances, Challenges and Opportunities" seeks to explore how emerging technologies are influencing the field of HCI. Contributions that provide theoretical insights and practical approaches to addressing the evolving needs of users in this rapidly changing technological landscape are encouraged.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • Interaction with AI agents in complex systems;
  • Collaboration between users and AI agents;
  • AI-driven personalized services and adaptive user interfaces;
  • Emerging interaction possibilities in VR/AR/MR environments;
  • New multi-modal interactions for natural user interfaces;
  • New user-centered design methodologies for intelligent systems;
  • Real-time prediction of user physiological states.

Dr. Yong Min Kim
Guest Editor

Manuscript Submission Information

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Keywords

  • user-centered design
  • intelligent systems
  • VR/AR/MR interaction
  • AI-driven personalization
  • adaptive user interfaces
  • collaboration with AI agents
  • autonomous systems
  • human–robot interaction

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Published Papers (1 paper)

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Research

25 pages, 1710 KB  
Article
Pedestrian Profiling Based on Road Crossing Decisions in the Presence of Automated Vehicles: The Sorting Hat for Pedestrian Behaviours and Psychological Facets
by Sachita Shahi, Ashim Kumar Debnath, Stewart Birrell, Ben Horan and William Payre
Appl. Sci. 2025, 15(18), 10105; https://doi.org/10.3390/app151810105 - 16 Sep 2025
Cited by 1 | Viewed by 549
Abstract
Automated Vehicles (AVs) are being developed with the aim to reduce the occurrence and severity of Road Traffic Crashes (RTCs). Studies suggest AVs may improve the safety of Vulnerable Road Users (VRUs), particularly on road crossings. However, exposure to novel technology over time [...] Read more.
Automated Vehicles (AVs) are being developed with the aim to reduce the occurrence and severity of Road Traffic Crashes (RTCs). Studies suggest AVs may improve the safety of Vulnerable Road Users (VRUs), particularly on road crossings. However, exposure to novel technology over time may lead to behavioural adaptation. Thus, understanding VRUs’ behavioural intentions towards AVs is crucial for their safe integration into traffic. We investigate four external factors pedestrians consider when crossing a road in front of an AV. An online questionnaire with 281 participants assessed crossing intentions, focusing on road gradient, weather, pedestrian–AV distance, and AV type. Personality traits and self-reported behaviour were measured. Anderson’s experimental protocol revealed all factors significantly influenced crossing decisions. Using hierarchical clustering followed by K-means clustering, the participants were classified into three different profiles: risk-averse, resolute, and indecisive pedestrians. We provide evidence of a strong link between crossing decisions, reported behaviours and psychological facets while interacting with an AV at crossings. Pedestrian profiling allows targeting preventative measures for groups based on unique characteristics, maximising efficiency thereof. Furthermore, pedestrian profiling can inform AV’s driving style to support safer road interactions. This is salient for resolute pedestrians, who take more risks, which may lead to severe RTCs. Full article
(This article belongs to the Special Issue Human-Computer Interaction: Advances, Challenges and Opportunities)
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