Multimodal Displays for Takeover Requests

Yang, Ji Hyun; Lee, Seul Chan; Nadri, Chihab; Kim, Jaewon; Shin, Jaekon; Jeon, Myounghoon

doi:10.1007/978-3-030-77726-5_15

Cited by 6 publications

(3 citation statements)

References 66 publications

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“…In this instance, drivers have more time to assess the situation and appropriately respond should the pedestrian decide to cross the road. Commonly, visual (e.g., flashing light), auditory (e.g., beep), and/or haptic cues are used to alert the driver about critical environmental information (Yang et al, 2022). However, these alerts can be unclear in their meaning, thus, may be interpreted differently between drivers.…”

Section: Introductionmentioning

confidence: 99%

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

Kettle,

Lee

2023

Proceedings of the Human Factors and Ergonomics Society Annual

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Numerous collisions have occurred since integrating vehicles with automated driving system (ADS) features. Attributed responsibility following collisions differ dependent on level of automation or anthropomorphism. However, gender differences are yet to be examined. Thus, the current study examined gender differences in responsibility assignment following collisions involving an ADS-equipped vehicle and the influence of a driving assistant (DA) that administered monitoring requests. Participants read hypothetical scenarios and watched corresponding simulated videos with or without the DA present before assigning blame to the human or the ADS. Hypotheses included gender differences in overall blame assignment, and interaction effects between gender and DA presence; gender and agent; and gender, DA presence, and agent. Results indicated gender differences when assigning responsibility to the human agent only. No other significant differences were supported indicating that men and women generally attribute blame similarly. However, further demographic differences (e.g., age, socio-economic status) should be explored.

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Section: Introductionmentioning

confidence: 99%

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

Kettle,

Lee

2023

Proceedings of the Human Factors and Ergonomics Society Annual

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“…Providing drivers with information about the vehicle's ADS status increases driver awareness [11]. Commonly, auditory, visual, and haptic alerts are used to quickly cue drivers about a critical environmental event [12]. However, these alerts can be ambiguous in meaning.…”

Section: Introductionmentioning

confidence: 99%

Impact of Monitoring Requests on Publics’ Assignment of Blame and Praise towards ADS Level 3 Vehicles

Kettle,

McCarty,

Simpson

et al. 2023

Human Behavior and Emerging Technologies

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As vehicle automation capabilities increase, driving control shifts from the human to the vehicle system. However, concerns arise regarding responsibility following critical events and the publics’ trust and acceptance of vehicles equipped with automated driving systems (ADS). The current study examined how participants assigned blame and praise to ADS-equipped vehicles and human drivers following collisions or near-misses and how these attributions were impacted by a virtual driving assistant that administered monitoring requests. Based on literature, our primary hypothesis was that more blame would be assigned to the human and more praise assigned to the ADS when the driving assistant was present. Additionally, we hypothesized greater reported trust towards ADS-equipped vehicles when the driving assistant was present. Participants read vignettes of automated driving, watched corresponding videos, and then self-reported trust, acceptance, anthropomorphism, and assignment of blame and praise. All hypotheses were supported indicating that significant effects were observed: participants assigned greater blame to the human when asked to actively monitor the driving environment and assigned greater praise to the ADS when it alerted the human driver. Additionally, participants reported greater trust and anthropomorphism of the ADS when the driving assistant was present. These findings suggest that explicitly communicating monitoring responsibility through a driving assistant significantly impacts the publics’ opinion of responsibility following critical events. These findings provide initial support for a solution to improve driver safety as well as policy implications regarding positive perceptions and the adoption of ADS-equipped vehicles.

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“…At these levels, autonomous systems still require drivers to resume manual control when the vehicle reaches its system limitations (e.g., entering construction sites or adverse weather). At this point, vehicles will alert the driver with a take-over request (TOR), which involves either visual, auditory, haptic, or a combination of sensory modalities (Yang et al, 2022). However, at level 3 and above, drivers may become out-of-the-loop and lose situational awareness of the driving environment by engaging in non-driving-related tasks after prolonged use; therefore, alerts to immediately resume manual control places the driver in potentially dangerous situations whilst discerning what is happening in the immediate environment (Petermeijer et al, 2017;Vlakveld et al, 2018;Zeeb et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Impact of Monitoring Requests on Trust, Acceptance, Blame, and Praise of Autonomous Vehicles

Kettle

Lee

2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Vehicles with autonomous features are more prevalent in today’s society, though as the level of autonomation increases, so does the vehicle system’s control of the vehicle. As the driving control shifts from human to the vehicle system, concerns arise regarding the attribution of responsibility and blame following critical events (e.g., collisions or near-misses). In this work-in-progress study, we aim to understand how the public attributes blame and praise to both humans and autonomous vehicles (AVs) following critical events. In addition, we examine how an AI driving assistant that administers Monitoring Requests influences blame and praise attributions. Furthermore, we examine differences in acceptance, trust, and perceived anthropomorphism between an AV with and without an AI driving assistant. Preliminary results are provided followed by a discussion of the expected results and potential impact for research and legal issues.

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Multimodal Displays for Takeover Requests

Cited by 6 publications

References 66 publications

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

Gender Differences in Responsibility Assignment Towards Level 3-ADS Vehicles

Impact of Monitoring Requests on Publics’ Assignment of Blame and Praise towards ADS Level 3 Vehicles

Impact of Monitoring Requests on Trust, Acceptance, Blame, and Praise of Autonomous Vehicles

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