Multimodal warning design for take-over request in conditionally automated driving

Abstract

Purpose Humans are required to respond to a vehicle’s request to take-over anytime even when they are not responsible for monitoring driving environments in automated driving, e.g., a SAE level-3 vehicle. Thus, a safe and effective delivery of a take-over request from an automated vehicle to a human is critical for the successful commercialization of automated vehicles. Methods In the current study, a set of human-in-the-loop experiments was conducted to compare diverse warning combinations by applying visual, auditory, and haptic modalities under systematically classified take-over request scenarios in conditionally automated driving. Forty-one volunteers consisting of 16 females and 25 males participated in the study. Vehicle and human data on response to take-over request were collected in two take-over scenarios, i.e., a disabled vehicle on the road ahead and a highway exit. Results Visual-auditory-haptic modal combination showed the best performance in both human behavioral and physiological data and visual-auditory warning in vehicle data. Visual-auditory-haptic warning combination showed the best performance when considering all performance indices. Meanwhile, visual-only warning, which is considered as a basic modality in manual driving, performed the worst in the conditionally automated driving situation. Conclusions These findings imply that the warning design in automated vehicles must be clearly differentiated from that of conventional manual driving vehicles. Future work shall include a follow-up experiment to verify the study results and compare more diverse multimodal combinations.

Towards Personalized 3D Augmented Reality Windshield Displays in the Context of Automated Driving

“…These findings are consistent with Abdi et al (2015). Another way to reduce take-over times with AR interfaces could be to not only use multimodal alerts (e.g., Yun and Yang, 2020), but also highlighting outside information that could cause a takeover (e.g., inattentive pedestrians) (Kim et al, 2016). From a research viewpoint, understanding (semi-)automated vehicle behavior, and leveraging novel interfaces to enrich in-vehicle experiences for drivers and passengers is an ongoing process in which we believe AR WSDs serve as an integral catalyst.…”

The Effects of Tactile Display on Automated Vehicle Takeover: A Literature Review

“…These studies utilized the driver's seat belt, seat pan, or wrists as the in-vehicle location in which to place the tactile display. A tactor would vibrate in response to a forward or rear-end collision threshold that was reached when the obstacle approached the participants' (ego) vehicle in a simulated or naturalistic driving environment (Huang & Pitts, 2022;Scott & Gray, 2008;Yun & Yang, 2020). For example, Ho, Tan, and Spence (2005) used a vibrotactile belt to represent imminent collision warnings in a driving simulator equipped with two tactors, one placed in front of the driver's torso and the other placed on the driver's lower back.…”

Development Status and Hotspot Visualized Analysis of Autonomous Vehicles Based on CiteSpace

“…e results show that when the driver is engaged in the visual secondary task, the steering response time increased significantly after take-over. To study how to safely and effectively transfer the take-over request of the autonomous driving to the driver, Yun and Yang [17] compared various warning combinations in the context of the take-over request classified by the system in conditional autonomous driving.…”