The effects of sitting postures on seat vibrotactile interaction system for enhancing occupants’ situation awareness in high-level automated driving
Year: 2025
Type: article
Abstract: This study investigated the effects of sitting postures on the enhancement of occupants’ situation awareness through seat vibrotactile interaction system in high-level automated driving scenarios during a non-driving related task. Furthermore, addressing the limitation of fixed, non-adaptive vibrotactile signal generation in existing studies, an occupant body pressure monitoring-based seat vibrotactile interaction system (OBPM-SVIS) was developed, and it was compared with the original system lacking the pressure monitoring function. The Wizard of Oz experimental approach was employed to simulate automated driving scenarios in real-road. Eighteen participants received signals indicating vehicle upcoming behaviors, including left turn, right turn, acceleration, and deceleration. The participants adopted five sitting postures, which were upright, left-leaning, right-leaning, backward-leaning, and forward-leaning. These signals were presented in both static and dynamic patterns. Effects were comprehensively evaluated based on correct response rate, reaction time, situation awareness rating technique (SART) score, rating scale mental effort (RSME) score, and user experience questionnaire (UEQ) score. Results indicated that non-upright sitting postures adversely affected the transmission of vibrotactile signals and increased the difficulty of signal recognition. Static pattern demonstrated less robustness to changes in sitting posture compared to dynamic pattern. The OBPM-SVIS effectively mitigated the adverse effects of sitting posture changes. This study provides a reference for optimizing vibrotactile interaction systems that convey information about the vehicle’s upcoming behaviors or takeover requests to occupants in high-level automated driving.
Authors: Chuanliang Shen, Xiaoyuan Ma, Longxu Zhang, Xiao Xiao, Yi Li, Hongyu Hu, Zhenhai Gao
Institution: Jilin University
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $2,990
Award: G4475271718
OpenAlex ID: W4415619625
