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RoadMind: Investigating Road-User’s Behaviour in Immersive Experiences

Sun, Ximeng LU and Sheng, Xiaoyu (2026) MAMM15 20261
Department of Design Sciences
Ergonomics and Aerosol Technology
Abstract
Understanding how drivers perceive and respond to traffic hazards is critical for designing safer road systems and human-centred autonomous vehicles. This study investigates hazard perception and driver behaviour in virtual reality (VR) driving environments through a multimodal approach. A VR simulation was developed using Unreal Engine and a Meta Quest Pro headset with integrated eye tracking, enabling controlled exposure to urban traffic scenarios. Eye tracking, head movement, and vehicle control data were collected from 17 participants across three urban areas of varying complexity.

The study examined how environmental complexity influences gaze behaviour, driving actions, and collision outcomes. Results indicate that hazard... (More)
Understanding how drivers perceive and respond to traffic hazards is critical for designing safer road systems and human-centred autonomous vehicles. This study investigates hazard perception and driver behaviour in virtual reality (VR) driving environments through a multimodal approach. A VR simulation was developed using Unreal Engine and a Meta Quest Pro headset with integrated eye tracking, enabling controlled exposure to urban traffic scenarios. Eye tracking, head movement, and vehicle control data were collected from 17 participants across three urban areas of varying complexity.

The study examined how environmental complexity influences gaze behaviour, driving actions, and collision outcomes. Results indicate that hazard detection failure is more closely associated with the spatial distribution of gaze than with overall gaze volume. Broader visual engagement was associated with reduced collisions in complex scenarios, while concentrated gaze and delayed reactions were more prevalent in collision events. Road geometry also emerged as a key factor: curved roads constrained environmental scanning and were linked to higher collision frequencies.

Based on these findings, a conceptual model is proposed describing the temporal relationship between environmental complexity, visual engagement, fixation timing, and collision probability. The study demonstrates the potential of integrating VR simulation and multimodal behavioural data for driving safety research, and identifies future directions including larger samples, enhanced simulation realism, and statistical validation. (Less)
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author
Sun, Ximeng LU and Sheng, Xiaoyu
supervisor
organization
course
MAMM15 20261
year
type
H2 - Master's Degree (Two Years)
subject
keywords
virtual reality, eye tracking, hazard perception, driver behaviour, multimodal analysis
language
English
id
9233305
date added to LUP
2026-06-10 10:34:31
date last changed
2026-06-10 10:34:31
@misc{9233305,
  abstract     = {{Understanding how drivers perceive and respond to traffic hazards is critical for designing safer road systems and human-centred autonomous vehicles. This study investigates hazard perception and driver behaviour in virtual reality (VR) driving environments through a multimodal approach. A VR simulation was developed using Unreal Engine and a Meta Quest Pro headset with integrated eye tracking, enabling controlled exposure to urban traffic scenarios. Eye tracking, head movement, and vehicle control data were collected from 17 participants across three urban areas of varying complexity.

The study examined how environmental complexity influences gaze behaviour, driving actions, and collision outcomes. Results indicate that hazard detection failure is more closely associated with the spatial distribution of gaze than with overall gaze volume. Broader visual engagement was associated with reduced collisions in complex scenarios, while concentrated gaze and delayed reactions were more prevalent in collision events. Road geometry also emerged as a key factor: curved roads constrained environmental scanning and were linked to higher collision frequencies.

Based on these findings, a conceptual model is proposed describing the temporal relationship between environmental complexity, visual engagement, fixation timing, and collision probability. The study demonstrates the potential of integrating VR simulation and multimodal behavioural data for driving safety research, and identifies future directions including larger samples, enhanced simulation realism, and statistical validation.}},
  author       = {{Sun, Ximeng and Sheng, Xiaoyu}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{RoadMind: Investigating Road-User’s Behaviour in Immersive Experiences}},
  year         = {{2026}},
}