The comparison of auditory, tactile, and multimodal warnings for the effective communication of unexpected events during an automated driving scenario

Geitner, Claudia; Biondi, Francesco; Skrypchuk, Lee; Jennings, Paul; Birrell, Stewart A.

doi:10.1016/j.trf.2019.06.011

Cited by 39 publications

(17 citation statements)

References 31 publications

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“…The communication of potential or actual hazards has been tested using diverse strategies, for example using visual (Wiegand et al, 2019), audible (Wong et al, 2019), haptic (Ma et al, 2019), olfactory (Wintersberger et al, 2019) and multimodal (Geitner et al, 2019) interfaces. Recent technological developments permit the construction of interfaces featuring augmented reality (AR).…”

Section: Literature Reviewmentioning

confidence: 99%

The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

Oliveira

Burns

Luton

et al. 2020

Transportation Research Part F: Traffic Psychology and Behaviou

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Section: Literature Reviewmentioning

confidence: 99%

The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

Oliveira

Burns

Luton

et al. 2020

Transportation Research Part F: Traffic Psychology and Behaviou

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“…Moreover, interactions with visual or audio-visual displays are more efficient than those with auditory displays only [36]. In this sense, research on multimodal perception is particularly relevant when studying human factors of driver aid systems [37,38].…”

Section: Human Factors and Their Limitsmentioning

confidence: 99%

Human–Machine Interface in Transport Systems: An Industrial Overview for More Extended Rail Applications

Enjalbert

Gandini

Baños³

et al. 2021

Machines

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This paper provides an overview of Human Machine Interface (HMI) design and command systems in commercial or experimental operation across transport modes. It presents and comments on different HMIs from the perspective of vehicle automation equipment and simulators of different application domains. Considering the fields of cognition and automation, this investigation highlights human factors and the experiences of different industries according to industrial and literature reviews. Moreover, to better focus the objectives and extend the investigated industrial panorama, the analysis covers the most effective simulators in operation across various transport modes for the training of operators as well as research in the fields of safety and ergonomics. Special focus is given to new technologies that are potentially applicable in future train cabins, e.g., visual displays and haptic-shared controls. Finally, a synthesis of human factors and their limits regarding support for monitoring or driving assistance is proposed.

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“…The theoretical basis of user cognition is mainly the theory of limited resources and graphic perception, which expresses the explicit resources and implicit cognition of VR system information representation. Due to the limited capacity of the user's cognitive resources, it is necessary to reduce a user's cognitive load through multiple channels during information identification [6,8,9], thus improving the cognitive efficiency of a user's experience and task operation scenarios. Therefore, this paper selects visual channels, auditory channels and tactile channels to study a user's cognitive behaviors and design resource characteristics.…”

Section: Channel Theory Of Cognitive Resourcesmentioning

confidence: 99%

“…Lei Xiao [8] et al summarized the use of tactile clues to interact with other sensory stimuli to predict potential perceptual experiences in multi-sensory environments. Geitner Claudia [9] and others extended the research on multimodal warning performances. The above research shows that the user's information perception ability in multi-channel is greater than that in single channel, so this paper divides the information input in VR system into three channels: visual, auditory and tactile.…”

Section: Introductionmentioning

confidence: 99%

Research on Optimization Method of VR Task Scenario Resources Driven by User Cognitive Needs

Fu¹,

Lv²,

Zhao³

et al. 2020

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Research was performed in order to improve the efficiency of a user’s access to information and the interactive experience of task selection in a virtual reality (VR) system, reduce the level of a user’s cognitive load, and improve the efficiency of designers in building a VR system. On the basis of user behavior cognition-system resource mapping, a task scenario resource optimization method for VR system based on quality function deployment-convolution neural network (QFD-CNN) was proposed. Firstly, under the guidance of user behavior cognition, the characteristics of multi-channel information resources in a VR system were analyzed, and the correlation matrix of the VR system scenario resource characteristics was constructed based on the design criteria of human–computer interaction, cognition, and low-load demand. Secondly, analytic hierarchy process (AHP)-QFD combined with evaluation matrix is used to output the priority ranking of VR system resource characteristics. Then, the VR system task scenario cognitive load experiment is carried out on users, and the CNN input set and output set data are collected through the experiment, in order to build a CNN system and predict the user cognitive load and satisfaction in the human–computer interaction in the VR system. Finally, combined with the task information interface of a VR system in a smart city, the application research of the system resource feature optimization method under multi-channel cognition is carried out. The results show that the test coefficient CR value of the AHP-QFD model based on cognitive load is less than 0.1, and the MSE of CNN prediction model network is 0.004247, which proves the effectiveness of this model. According to the requirements of the same design task in a VR system, by comparing the scheme formed by the traditional design process with the scheme optimized by the method in this paper, the results show that the user has a lower cognitive load and better task operation experience when interacting with the latter scheme, so the optimization method studied in this paper can provide a reference for the system construction of virtual reality.

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The comparison of auditory, tactile, and multimodal warnings for the effective communication of unexpected events during an automated driving scenario

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 39 publications

References 31 publications

The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

The influence of system transparency on trust: Evaluating interfaces in a highly automated vehicle

Human–Machine Interface in Transport Systems: An Industrial Overview for More Extended Rail Applications

Research on Optimization Method of VR Task Scenario Resources Driven by User Cognitive Needs

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