Takeover and Handover Requests using Non-Speech Auditory Displays in Semi-Automated Vehicles

Kutchek, Kyle; Jeon, Myounghoon

doi:10.1145/3290607.3313078

Cited by 14 publications

(1 citation statement)

References 4 publications

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“…We applied unimodal advisory warning rather than multimodal modalities. While multimodal modalities were found to improve reaction time [44] and quality of takeover [37], prior studies reported them as urgent [25] and annoying [45]. We utilized unimodal modalities (1) to avoid resource sharing conflicts according to Wickens' multiple resource theory [58], (2)to investigate the impact of non-assertive advisory warnings on takeover behavior.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving

Pakdamanian

Sheng

et al. 2022

Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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Section: Limitations and Future Workmentioning

confidence: 99%

Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving

Pakdamanian

Sheng

et al. 2022

Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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Multimodal Displays for Takeover Requests

Yang

Lee

Nadri

et al. 2022

Studies in Computational Intelligence

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How Older Drivers Perceive Warning Alerts? Insights for the Design of Driver–Car Interaction

Rukonić

Mwange²,

Kieffer

2022

SN COMPUT. SCI.

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The automotive industry is working toward driving automation and driver-assistance technology is becoming a norm in modern cars. Warning alert systems support the driver–car interaction and inform drivers about automation system status, upcoming obstacles, or dangers ahead. However, older drivers’ needs are not always addressed in research studies, although they make up a large segment of drivers. Therefore, we conducted a qualitative three-round formative evaluation of a warning alert system using video prototypes in lab and remote settings. The goal was to evaluate visual-, sound-, and speech-based alerts based on: (a) their efficiency in informing drivers about the road situation ahead, and (b) participants’ subjective opinions. We evaluated the system’s efficiency using self-reported data measuring participants’ cognitive load, usability, UX, and ease of use. Also, we conducted interviews to collect subjective feedback about proposed prototypes. In this article, we describe the design of warning alerts and report on their evaluation results. Our results show that speech-based warnings, especially when coupled with visual warnings, are efficient and accepted well by the participants. This article illustrates older drivers’ attitude toward the use of different warning modalities in the driving context.

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Takeover and Handover Requests using Non-Speech Auditory Displays in Semi-Automated Vehicles

Cited by 14 publications

References 4 publications

Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving

Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving

Multimodal Displays for Takeover Requests

How Older Drivers Perceive Warning Alerts? Insights for the Design of Driver–Car Interaction

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