TY - GEN
T1 - ReAR Indicators
T2 - 2024 International Conference on Advanced Visual Interfaces, AVI 2024
AU - Zhao, Guanghan
AU - Hu, Xiaodan
AU - Orlosky, Jason
AU - Kiyokawa, Kiyoshi
N1 - Publisher Copyright:
© 2024 ACM.
PY - 2024/6/3
Y1 - 2024/6/3
N2 - During cycling activities, cyclists often focus on pedestrians, vehicles or road conditions in front of their bicycle. Because of this forward focus, approaching vehicles from behind can easily be missed, which can result in accidents, injury, or death. Although rear information can viewed with handle-mounted mirrors or monitors, looking down can distract the cyclist from other hazards. To help address this problem, we present the ReAR Indicator, a peripheral information delivery approach that enhances awareness of rear-approaching vehicles and at the same time preserves forward vision. ReAR uses computer vision applied to a rear-facing RGB-D camera and combines it with position data from a head mounted display for real-time vehicle detection and visualization. Our algorithm delivers information to the periphery such that the user can simultaneously view forward information but still use cues that provide information about hazard distance, width, and probability of collision. Results from a virtual reality based experiment with 20 participants showed that the ReAR Indicator helped cyclists maintain a forward focus while still avoiding collisions with rear-approaching vehicles and in some conditions either matched or outperformed 3D arrows and virtual monitors.
AB - During cycling activities, cyclists often focus on pedestrians, vehicles or road conditions in front of their bicycle. Because of this forward focus, approaching vehicles from behind can easily be missed, which can result in accidents, injury, or death. Although rear information can viewed with handle-mounted mirrors or monitors, looking down can distract the cyclist from other hazards. To help address this problem, we present the ReAR Indicator, a peripheral information delivery approach that enhances awareness of rear-approaching vehicles and at the same time preserves forward vision. ReAR uses computer vision applied to a rear-facing RGB-D camera and combines it with position data from a head mounted display for real-time vehicle detection and visualization. Our algorithm delivers information to the periphery such that the user can simultaneously view forward information but still use cues that provide information about hazard distance, width, and probability of collision. Results from a virtual reality based experiment with 20 participants showed that the ReAR Indicator helped cyclists maintain a forward focus while still avoiding collisions with rear-approaching vehicles and in some conditions either matched or outperformed 3D arrows and virtual monitors.
KW - Cycling
KW - Safety
KW - User Interface
UR - http://www.scopus.com/inward/record.url?scp=85195418307&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85195418307&partnerID=8YFLogxK
U2 - 10.1145/3656650.3656659
DO - 10.1145/3656650.3656659
M3 - Conference contribution
AN - SCOPUS:85195418307
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 2024 International Conference on Advanced Visual Interfaces, AVI 2024
PB - Association for Computing Machinery
Y2 - 3 June 2024 through 7 June 2024
ER -