Ghost driver

Rothenbücher, Dirk; Li, Jamy; Sirkin, David; Mok, Brian; Ju, Wendy

doi:10.1145/2809730.2809755

Cited by 39 publications

(3 citation statements)

References 6 publications

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“…Many recent studies on vehicles in HCI focus on humanvehicle interaction [15], including driver-vehicle interaction [3,6] and pedestrian-vehicle interaction [1,16]. Among these, Eguchi et al prototyped an autonomous vehicle having soft and inflatable exterior that could notify a pedestrian of which driving mode (i.e., manual or autonomous) was being used, by changing the body shape [4].…”

Section: Vehicles In Hcimentioning

confidence: 99%

poimo

Niiyama

Sato

Tsujimura

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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Despite the recent growth in popularity of personal mobility devices (e.g., e-scooters and e-skateboards), they still suffer from limited safety and narrow design form factors, due to their rigid structures. On the other hand, inflatable interfaces studied in human-computer interaction can achieve large volume change by simple inflation/deflation. Inflatable structure also offers soft and safe interaction owing to material compliance and diverse fabrication methods that lead to a wide range of forms and aesthetics. In this paper, we propose poimo, a new family of POrtable and Inflatable MObility devices, which consists of inflatable frames, inflatable wheels, and inflatable steering mechanisms made of a mass-manufacturable material called drop-stitch fabric. First, we defined the basic material properties of a drop-stitch inflatable structure that is sufficiently strong to carry a person while simultaneously allowing soft deformation and deflation for storage and portability. We then implemented an interactive design system that can scan the user's desired riding posture to generate a customized personal mobility device and can add the user's shape and color preferences. To demonstrate the custom-design capability and mobility, we designed several 3D models using our system and built physical samples for two basic templates: a motorcycle and a wheelchair. Finally, we conducted an online user study to examine the usability of the design system and share lessons learned for further improvements in the design and fabrication of poimo.

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Section: Vehicles In Hcimentioning

confidence: 99%

poimo

Niiyama

Sato

Tsujimura

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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“…This application of the WoZ method is used both in driving simulators ( Schieben et al, 2009 ) and with real vehicles on test tracks ( Pipkorn et al, 2021 ) and on public roads ( Jarosch et al, 2019a ). Researchers have built numerous other WoZ vehicles to simulate Level 2 through 5 driving automation systems to study a broad array of research topics, including non-driving task engagement during unsupervised automation ( Klingegård et al, 2020 ), drive takeover performance during CAD ( Purucker et al, 2018 ), interactions between vulnerable road users and autonomous vehicles ( Rothenbücher et al, 2015 ; Li et al, 2020 ), and communication between autonomous vehicles and vulnerable road users via external human-machine interfaces ( Chen et al, 2020 ; Faas and Baumann, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Do you trust me? Driver responses to automated evasive maneuvers

et al. 2023

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An increasing number of Conditionally Automated Driving (CAD) systems are being developed by major automotive manufacturers. In a CAD system, the automated system is in control of the vehicle within its operational design domain. Therefore, in CAD the vehicle is capable of tactical control of the vehicle and needs to be able to maneuver evasively by braking or steering to avoid objects. During these evasive maneuvers, the driver may attempt to take back control of the vehicle by intervening. A driver interrupting a CAD vehicle while properly performing an evasive maneuver presents a potential safety risk. To investigate this issue, 36 participants were recruited to participate in a Wizard-of-Oz research study. The participants experienced one of two evasive maneuvers of moderate intensity on a test track. The evasive maneuver required the CAD system to brake or steer to avoid the box placed in the lane of travel of the test vehicle. Drivers glanced toward the obstacle but did not intervene or prepare to intervene in response to the evasive maneuver. Importantly, the drivers who chose to intervene did so safely. These findings suggest that after experiencing a CAD vehicle for a brief period, most participants trusted the system enough to not intervene during a system-initiated evasive maneuver.

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“…Of immediate interest are risk factors that might suppress or alter intervention by bystanders. Concerns about personal risk in close quarters have been seen for autonomous vehicles [2].…”

Section: Introductionmentioning

confidence: 99%

Personal Safety is More Important Than Cost of Damage During Robot Failure

Adubor

John

Steinfeld

2017

Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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As robots become more common in everyday life it will be increasingly important to understand how non-experts will view robot failure. In this study, we found that severity of failure seems to be tightly coupled with perceived risk to self rather than risk to the robot's task and object. We initially thought perceived severity would be tied to the cost of damage. Instead, participants placed falling drinking glasses above a laptop when rating the severity of the failure. Related results reinforce the primacy of personal safety over the financial cost of damage and suggest the results were tied to proximity to breaking glass. 1

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Ghost driver

Cited by 39 publications

References 6 publications

poimo

poimo

Do you trust me? Driver responses to automated evasive maneuvers

Personal Safety is More Important Than Cost of Damage During Robot Failure

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