Comparing Smart Ring and Glove Wearable Interfaces for Takeover Requests in Automated Driving
A driving simulator experiment comparing ring, glove, and seat-back vibrotactile takeover-request interfaces, and the information types and request structures delivered through them.
Overview
This project investigated how wearable vibrotactile takeover-request interfaces could support driver takeover performance in SAE Level 3 automated driving. We compared ring-, glove-, and seat-back vibration interfaces while also examining different information types and takeover-request structures in a driving simulator study.
Problem Statement
Level 3 automated driving requires drivers to quickly transition from non-driving activities back to manual control when a takeover request occurs. However, existing tactile warning interfaces can be sensitive to posture and device placement.
This study explored whether wearable vibrotactile devices, including rings and gloves, could provide a more effective way to support driver takeover.
Research Focus
The goal of the present study was to investigate the effects of device type, TOR structure, and information type on drivers' takeover performance in time-critical automated driving situations.
Method
The experiment used a 5 × 2 × 2 full factorial design to examine how wearable device type, takeover-request structure, and information type influenced takeover performance.
Forty licensed drivers (24 female, 16 male) were recruited from the SJSU SONA participant pool. Participants ranged from 18 to 64 years old (M = 24.57) and drove an average of 3.98 days per week.
Participants completed the study in a driving simulator using an SAE Level 3 automated driving scenario. The automated vehicle traveled in the middle lane of a three-lane highway while participants watched YouTube videos as a non-driving-related task. Vibrotactile takeover cues were delivered through five interface configurations: one ring, two rings, one glove, two gloves, and a seat-back vibration baseline.
Participants traveled in the middle lane of a three-lane highway under automated driving while watching YouTube videos as a non-driving-related task. When an obstacle appeared ahead, a takeover request prompted the driver to resume manual control and move into the open adjacent lane.
We evaluated takeover performance and participants' subjective experience using both objective and subjective measures.
Objective Measures
Takeover Time: Time required to respond to the takeover request. Shorter times indicate faster responses.
Information Processing Time: Time required to process the takeover information and select an action. Shorter times indicate faster information processing.
Maximum Resulting Acceleration: Maximum acceleration during the takeover maneuver. Lower values indicate smoother vehicle control.
Subjective Measures
Workload: Participants’ perceived workload during each condition. Higher scores indicate greater workload.
Acceptance: Participants’ perceived usefulness and satisfaction with the interface. Higher scores indicate greater acceptance.
Results & Discussion
Two-step takeover requests sped up responses but introduced trade-offs, while device configuration and information type shaped how useful the interface felt more than objective performance.
- Two-step TOR led to shorter takeover time and information-processing time.
- But it also led to higher maximum resulting acceleration.
- Two-step TOR received lower usefulness ratings.
- Its workload effect depended on information type.
- Two-step TORs led to faster responses after the tactile cue.
- The pre-warning may have helped drivers reorient earlier.
- However, faster responses did not improve overall takeover quality.
- Two-step TORs also showed a subjective trade-off, with lower usefulness and higher workload in the instructional condition.
- Device configuration did not affect objective performance.
- Usefulness: two-glove > two-ring.
- Satisfaction: two-glove > one-glove.
- All devices provided clear directional information after training.
- Two-glove and two-ring showed higher usefulness ratings, which may reflect better spatial mapping of the tactile cues.
- Glove devices may also have been more comfortable because the tactors fit better on the back of the hand.
- Information type did not affect objective performance.
- Informative cues received higher usefulness ratings than instructional cues.
- Both cue types supported similar objective performance after training.
- Informative cues received higher usefulness ratings, perhaps because they provided more context about the driving environment.
- In the instructional condition, the pre-warning may have felt redundant and increased workload.
Limitations
References
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