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Heena Noh

dblp:330/9142 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 77% Human-robot interaction · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments
pedestrian safety
0.912025
Proximity Zones Based on Perceived Danger in Human-Robot Interaction · HRI 2025

Methods — techniques the papers use, named apart from their topics

within-subject design · 0.9virtual reality experiment · 0.9
YearPublicationVenuePosition
2025 Proximity Zones Based on Perceived Danger in Human-Robot Interaction
abstract
This study addresses the challenge of ensuring pedestrian safety in shared spaces during human-robot interactions. As mobile robots become increasingly integrated into public environments, there is a need to better understand how pedestrians perceive robots in proximity. This research explores the effects of robot lateral distance, robot velocity, and pedestrian state on pedestrian perception, with a particular focus on proximity zones during human-robot interactions. Conducted in a virtual reality environment with a within-subject design, the study measured perceived danger through button presses and visualized proximity zones using contour density plots. Findings reveal that increasing lateral distance significantly decreases button press likelihood, particularly beyond 160 cm. Robot velocities of 1 mls and 1.5 mls showed no significant difference, suggesting pedestrians perceive them similarly due to their alignment with average walking speed. Proximity zones were consistently wider and denser on the left than the right, highlighting spatial asymmetry in perception. These results provide quantitative and visual insights for designing mobile robots in shared spaces. Future research should examine environmental and group dynamics and robot design to enhance safety and public acceptance in human-robot interactions.
Suhwan Jung, Hyochang Kim 0001, Hyunmin Kang, Meen Jong Kim, Heena Noh, Yong Gu Ji
HRI5