Image parameters for driving with indirect viewing systems

Erp, J.B.F. van; Padmos, P.

doi:10.1080/0014013032000121624

Cited by 67 publications

(38 citation statements)

References 26 publications

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“…Therefore, applying an alternative modality to free the eyes and ears of the user is a relevant issue. A similar trend can be seen in the design of user interfaces where alternative displays are being developed to lessen the risk of visual and/or auditory overload in, for instance, car driving [19]. The use of tactile displays is one of these alternatives.…”

Section: Introductionmentioning

confidence: 90%

Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Brouwer¹,

Erp²,

Aloise

et al. 2010

SRX Neuroscience

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The P300 is a positive peak in EEG occurring after presentation of a target stimulus. For brain-computer interfaces (BCIs), eliciting P300s by tactile stimuli would have specific advantages; the display can be hidden under clothes and keeps the user's gaze free. In addition, robust classification is especially important for BCIs. This motivated us to investigate P300s in response to tactile and visual stimuli unimodally and bimodally. Tactile stimuli were delivered by tactors around the participant's waist. Visual stimuli were flashed circles on a monitor, schematically representing the tactors. Participants attended to the vibrations and/or flashes of a "target" presented in a stream of standards. The P300 amplitude for the different modalities was comparable in size and depended on electrode location. Classification accuracy was highest in the bimodal condition. We conclude that bimodal stimuli could enhance classification results within a BCI context compared to unimodal presentations.

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Section: Introductionmentioning

confidence: 90%

Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Brouwer¹,

Erp²,

Aloise

et al. 2010

SRX Neuroscience

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show abstract

“…The data of influencing criteria for the design of driver's seat and rear-view mirror which are given in Table 3 and Table 4 are normalized using equation (12). The normalized decision matrix is shown in Table 5. After that, the weighted normalized decision matrix (W WNM ) is determined using equation (12).…”

Section: Determining the Influencing Variables Of Rear-view Mirror Dementioning

confidence: 99%

“…Moreover, major accidents were caused when the target vehicle appeared in the driver's blind spot during lane change or crowded urban travelling and the driver did not carefully observe the approaching vehicle from the rear and side mirrors [11]. Jan and Pieter [12] studied the use of cameras to support drivers under low visibility conditions or/and in the blind spot area.…”

Section: Review On Optimization Of Design Parameters Of Rear-view Mirrormentioning

confidence: 99%

“…The normalized decision matrix is shown in Table 5. After that, the weighted normalized decision matrix (W WNM ) is determined using equation (12). Next, the positive ideal solution (V j * ) and negative ideal solution (V j -) are taken from the W WNM and the separation measures are calculated from the ideal solution using equation (13).…”

Section: Determining the Influencing Variables Of Rear-view Mirror Dementioning

confidence: 99%

“…where, X ij is the i th criterion for j th alternative Step 3 -Calculation of the weighted normalized decision matrix: The weighted normalized decision matrix (W WNM ) is determined by multiplying the normalized decision matrix by its associated weights (W ij ) which are calculated using equation (12). Step 4 -Building of positive and negative ideal solutions: The positive ideal solution corresponds to the set of best or maximum values of each column.…”

Section: Topsismentioning

confidence: 99%

See 2 more Smart Citations

Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

Pandian¹,

Sundaram

Rajakarunakaran³

2016

PROMET

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Statistics reveals that the visual problems are the primereasons for a larger number of road accidents. The blind spotis the major problem related to vision. The aim of this studyis to develop a fuzzy-based multi criteria decision-makingmodel for optimizing the area of the blind spot in the frontand sides of a heavy transport vehicle. To achieve this, thestatistical tool ANOVA (Analysis of Variance) and multi criteriaoptimization techniques like TOPSIS (Technique for Orderof Preference by Similarity to Ideal Solution), FAHP (FuzzyAnalytical Hierarchy Process) and GRA (Grey RelationalAnalysis) were also used in this problem This paper consistsof three modules: first, the blind spots of the existing bodystructure dimension used in heavy vehicles were studiedand the optimal design parameters were determined by usingANOVA and TOPSIS methodologies; next, the weights ofthe design parameters were calculated using FAHP method.Finally, GRA-based Multi Criteria Decision Making (MCDM)approach has been used to rank the vehicle body structures.The proposed model has been implemented in a transportcorporation to compare four different types of body structuresand concluded that the body structure which was builtby an outsourced body builder is having a smaller area ofblind spot and optimal design parameters as well.

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Tactile Stimulation

Poletto¹

2006

Encyclopedia of Medical Devices and Instrumentation

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Tactile stimulators manipulate sensors in the skin to produce sensations such as light touch, vibration, pressure, shape, and texture. The wide variety of applications for tactile stimulation include sensory substitution and augmentation, telepresence and telerobotic sensory feedback, improved immersion in virtual environments, and general information communication through the skin senses. This article discusses the three primary classes of tactile stimulation technologies: vibrotaction, dynamic mechanical shape arrays, and electrocutaneous stimulation. An overview of basic mechanoreceptor physiology is provided, including implications for stimulator design parameters. Predictions for the future development of tactile stimulation are presented, including the emerging applications in wearable computers.

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Image parameters for driving with indirect viewing systems

Cited by 67 publications

References 26 publications

Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Tactile, Visual, and Bimodal P300s: Could Bimodal P300s Boost BCI Performance?

Development of Fuzzy Based Intelligent Decision Model to Optimize the Blind Spots in Heavy Transport Vehicles

Tactile Stimulation

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