TY - GEN
T1 - Enhancing Safety and User Experience in Automated Driving
T2 - 34th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2025
AU - Liu, Yang
AU - Shangguan, Zhegong
AU - Tapus, Adriana
AU - Safin, Stéphane
AU - Détienne, Francoise
AU - Lecolinet, Eric
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - The seamless transition of control between drivers and autonomous systems remains a critical challenge in automated driving, affecting both safety outcomes and overall user experience. To address this challenge, our study examines the effectiveness of two distinct haptic feedback approaches - pneumatic and vibrotactile - when implemented as intelligent interface components for takeover requests (TORs) during these transition periods. We specifically investigate how these haptic modalities can effectively signal drivers when human intervention is required, facilitating smoother control transitions from automated to manual driving. We designed a comprehensive experimental setup integrating these haptic modalities with audio and visual cues and evaluated their performance across nine interaction tasks to understand how multi-modal feedback influences driver responsiveness during takeover scenarios. Our findings reveal that multi-modal approaches incorporating either pneumatic or vibrotactile feedback, combined with standard visual cues, substantially outperform audio-only alerts in both response time and accuracy metrics for takeover requests (TORs). Notably, pneumatic feedback offered more natural sensation and smoother transitions than vibrotactile feedback, with pneumatic systems excelling in comfort while vibrotactile feedback better serves urgent takeovers. This first systematic comparison provides valuable insights for developing interfaces that balance effectiveness with comfort in human-machine systems.
AB - The seamless transition of control between drivers and autonomous systems remains a critical challenge in automated driving, affecting both safety outcomes and overall user experience. To address this challenge, our study examines the effectiveness of two distinct haptic feedback approaches - pneumatic and vibrotactile - when implemented as intelligent interface components for takeover requests (TORs) during these transition periods. We specifically investigate how these haptic modalities can effectively signal drivers when human intervention is required, facilitating smoother control transitions from automated to manual driving. We designed a comprehensive experimental setup integrating these haptic modalities with audio and visual cues and evaluated their performance across nine interaction tasks to understand how multi-modal feedback influences driver responsiveness during takeover scenarios. Our findings reveal that multi-modal approaches incorporating either pneumatic or vibrotactile feedback, combined with standard visual cues, substantially outperform audio-only alerts in both response time and accuracy metrics for takeover requests (TORs). Notably, pneumatic feedback offered more natural sensation and smoother transitions than vibrotactile feedback, with pneumatic systems excelling in comfort while vibrotactile feedback better serves urgent takeovers. This first systematic comparison provides valuable insights for developing interfaces that balance effectiveness with comfort in human-machine systems.
UR - https://www.scopus.com/pages/publications/105024539796
U2 - 10.1109/RO-MAN63969.2025.11217837
DO - 10.1109/RO-MAN63969.2025.11217837
M3 - Conference contribution
AN - SCOPUS:105024539796
T3 - IEEE International Workshop on Robot and Human Communication, RO-MAN
SP - 622
EP - 628
BT - 2025 34th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2025
PB - IEEE Computer Society
Y2 - 25 August 2025 through 29 August 2025
ER -