scholarly journals A Review of Occlusion as a Tool to Assess Attentional Demand in Driving

2021 ◽  
pp. 001872082110109
Author(s):  
Tuomo Kujala ◽  
Katja Kircher ◽  
Christer Ahlström
Keyword(s):  
Visual Information ◽  
Attentional Demand ◽  
Detection Algorithms ◽  
Visual Occlusion ◽  
Vehicle System ◽  
Information Sampling ◽  
Occlusion Technique ◽  
Naturalistic Driving ◽  
Human Factors Research ◽  
Selection Of

Objective The aim of this review is to identify how visual occlusion contributes to our understanding of attentional demand and spare visual capacity in driving and the strengths and limitations of the method. Background The occlusion technique was developed by John W. Senders to evaluate the attentional demand of driving. Despite its utility, it has been used infrequently in driver attention/inattention research. Method Visual occlusion studies in driving published between 1967 and 2020 were reviewed. The focus was on original studies in which the forward visual field was intermittently occluded while the participant was driving. Results Occlusion studies have shown that attentional demand varies across situations and drivers and have indicated environmental, situational, and inter-individual factors behind the variability. The occlusion technique complements eye tracking in being able to indicate the temporal requirements for and redundancy in visual information sampling. The proper selection of occlusion settings depends on the target of the research. Conclusion Although there are a number of occlusion studies looking at various aspects of attentional demand, we are still only beginning to understand how these demands vary, interact, and covary in naturalistic driving. Application The findings of this review have methodological and theoretical implications for human factors research and for the development of distraction monitoring and in-vehicle system testing. Distraction detection algorithms and testing guidelines should consider the variability in drivers’ situational and individual spare visual capacity.

scholarly journals On the Difference Between Necessary and Unnecessary Glances Away From the Forward Roadway: An Occlusion Study on the Motorway

2019 ◽  
Vol 62 (7) ◽  
pp. 1117-1131 ◽  
Author(s):  
Katja Kircher ◽  
Tuomo Kujala ◽  
Christer Ahlström
Keyword(s):  
Visual Information ◽  
Situational Factors ◽  
Minimum Amount ◽  
Safe Driving ◽  
Detection Algorithms ◽  
Visual Occlusion ◽  
Visual Sampling ◽  
Naturalistic Driving ◽  
The Difference

Objective The present study strove to distinguish traffic-related glances away from the forward roadway from non-traffic-related glances while assessing the minimum amount of visual information intake necessary for safe driving in particular scenarios. Background Published gaze-based distraction detection algorithms and guidelines for distraction prevention essentially measure the time spent looking away from the forward roadway, without incorporating situation-based attentional requirements. Incorporating situation-based attentional requirements would entail an approach that not only considers the time spent looking elsewhere but also checks whether all necessary information has been sampled. Method We assess the visual sampling requirements for the forward view based on 25 experienced drivers’ self-paced visual occlusion in real motorway traffic, dependent on a combination of situational factors, and compare these with their corresponding glance behavior in baseline driving. Results Occlusion durations were on average 3 times longer than glances away from the forward roadway, and they varied substantially depending on particular maneuvers and on the proximity of other traffic, showing that interactions with nearby traffic increase perceived uncertainty. The frequency of glances away from the forward roadway was relatively stable across proximity levels and maneuvers, being very similar to what has been found in naturalistic driving. Conclusion Glances away from the forward roadway proved qualitatively different from occlusions in both their duration and when they occur. Our findings indicate that glancing away from the forward roadway for driving purposes is not the same as glancing away for other purposes, and that neither is necessarily equivalent to distraction.

Data characterization for automatic selection of valve stiction detection algorithms

2013 ◽  
Author(s):  
Alexey Zakharov ◽  
Elena Zattoni ◽  
Lei Xie ◽  
Octavio Pozo ◽  
Sirkka-Liisa Jamsa-Jounela
Keyword(s):  
Detection Algorithms ◽  
Automatic Selection ◽  
Valve Stiction ◽  
Selection Of

scholarly journals Selection of visual information for lightness judgements by eye movements

2013 ◽  
Vol 368 (1628) ◽  
pp. 20130056 ◽  
Author(s):  
Matteo Toscani ◽  
Matteo Valsecchi ◽  
Karl R. Gegenfurtner
Keyword(s):  
Eye Movements ◽  
Visual System ◽  
Visual Information ◽  
Selection Process ◽  
Sampling Strategy ◽  
Selection Strategy ◽  
Eye Fixations ◽  
Target Layer ◽  
Highly Correlated ◽  
Selection Of

When judging the lightness of objects, the visual system has to take into account many factors such as shading, scene geometry, occlusions or transparency. The problem then is to estimate global lightness based on a number of local samples that differ in luminance. Here, we show that eye fixations play a prominent role in this selection process. We explored a special case of transparency for which the visual system separates surface reflectance from interfering conditions to generate a layered image representation. Eye movements were recorded while the observers matched the lightness of the layered stimulus. We found that observers did focus their fixations on the target layer, and this sampling strategy affected their lightness perception. The effect of image segmentation on perceived lightness was highly correlated with the fixation strategy and was strongly affected when we manipulated it using a gaze-contingent display. Finally, we disrupted the segmentation process showing that it causally drives the selection strategy. Selection through eye fixations can so serve as a simple heuristic to estimate the target reflectance.

scholarly journals SIMULATORS FOR TRAINING OF VEHICLES’ DRIVERS: INFORMATION MODELS’ ANALYSIS (REVIEW)

2019 ◽  
Vol 16 (5) ◽  
pp. 558-571
Author(s):  
A. V. Belyakova ◽  
B. V. Saveliev
Keyword(s):  
Visual Information ◽  
Educational Process ◽  
Vehicle Safety ◽  
Driver Training ◽  
Advantages And Disadvantages ◽  
Information Models ◽  
Initial Stage ◽  
Vestibular Information ◽  
Selection Of

Introduction. Organization of high-quality training of the vehicles’ drivers is possible only with the proper formation of professional skills. Moreover, the formation of the skills is necessary for the driver to control the vehicle safety, perhaps by using simulators at the initial stage of training. The use of simulators allows automating the actions that the driver performs, while not exposing the student to risks.Therefore, the purpose of the paper is to analyze the application of simulators in the training of the vehicles’ drivers.Materials and methods. The paper presented the basic psycho physiological principles of the learning process, which should be taken into account when using simulators for driver training. The authors demonstrated the classification of the car simulators used for training of drivers by the information models. Existing information models of simulators were divided into two groups: reproducing only visual information, without imitation of the vestibular and simulating both visual and vestibular information. The analysis reflected the advantages and disadvantages of information models.Results. As a result, the authors proposed two systematizing features: the view angle of the visual information and the simulation of vestibular information.Discussion and conclusions. The research is useful not only for the further science development, but also for the selection of simulators and for the organization of the educational process in driving schools.

scholarly journals Research on Robustness of Related Images for Power Equipment Inspection

2021 ◽  
Vol 2113 (1) ◽  
pp. 012045
Author(s):  
Chunlei Zhou ◽  
Xiangzhou Chen ◽  
Wenli Liu ◽  
Tianyu Dong ◽  
Huang Yun
Keyword(s):  
Deep Learning ◽  
Image Recognition ◽  
Feature Fusion ◽  
Power Equipment ◽  
Actual Measurement ◽  
Practical Applications ◽  
Detection Algorithms ◽  
Traction Substations ◽  
Deep Learning Model ◽  
Selection Of

Abstract With the increase in the number of traction substations year by year, manual inspections are gradually being replaced by unattended inspections. Target detection algorithms based on deep learning are more widely used in intelligent inspections of power equipment. However, in practical applications, it is found that due to the small target to be detected, the accuracy of the deep learning model will decrease when the shooting angle is inclined and the light conditions are poor. This is because the algorithm’s robustness is low, and the detection ability of the model will be seriously affected when the angle or illumination difference with the sample is large. Based on this, the feature fusion part of the YOLOv3 algorithm and the selection of the loss function and the size of the anchor frame are improved, and the improved ASFF fusion method is used to classify various images in the power equipment. Actual measurement and repeated experiments show that the proposed method can be effectively applied to image recognition of various power equipment, optimize robustness, and greatly improve the image recognition efficiency of power equipment.

scholarly journals A New Image Registration Algorithm Based on Evidential Reasoning

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1091 ◽  
Author(s):  
Zhe Zhang ◽  
Deqiang Han ◽  
Jean Dezert ◽  
Yi Yang
Keyword(s):  
Image Registration ◽  
Fundamental Problem ◽  
Similarity Measures ◽  
Detection Algorithms ◽  
Image Registration Algorithm ◽  
Theory Of Belief Functions ◽  
Pros And Cons ◽  
Registration Result ◽  
Different Levels ◽  
Selection Of

Image registration is a crucial and fundamental problem in image processing and computer vision, which aims to align two or more images of the same scene acquired from different views or at different times. In image registration, since different keypoints (e.g., corners) or similarity measures might lead to different registration results, the selection of keypoint detection algorithms or similarity measures would bring uncertainty. These different keypoint detectors or similarity measures have their own pros and cons and can be jointly used to expect a better registration result. In this paper, the uncertainty caused by the selection of keypoint detector or similarity measure is addressed using the theory of belief functions, and image information at different levels are jointly used to achieve a more accurate image registration. Experimental results and related analyses show that our proposed algorithm can achieve more precise image registration results compared to several prevailing algorithms.

A Knowledge-Based Tool for the Selection of Design Options During the Competitive Tendering of Vehicle Systems

Volume 3 ◽  
2004 ◽  
Author(s):  
Clive I. Kerr ◽  
Rajkumar Roy ◽  
Peter J. Sackett
Keyword(s):  
Automotive Industry ◽  
Proof Of Concept ◽  
Competitive Tendering ◽  
Knowledge Based ◽  
Vehicle System ◽  
Tier 1 ◽  
Vehicle Systems ◽  
Design Options ◽  
Selection Of

In the automotive industry the activities of documenting the design options and generating the necessary request for quotations, for Tier 1 system suppliers to be awarded contracts for design and development, is complex and time-consuming since these activities are predominately manual and paper-based. Thus, a knowledge-based tool is being developed to aid the selection of the design options for vehicle systems during competitive tendering. The tool is based on ontologies in order to provide a common and shared definition for the options available for a given vehicle system. An overview of this approach is provided and, as a ‘proof of concept’, a case study involving seating systems is presented. This paper shows, through the seating system case study, how the functionalities and features of a vehicle system can be selected and documented in order to streamline the business process of contracting out product development through the supply chain.

scholarly journals Spatial Attention Evokes Similar Activation Patterns for Visual and Auditory Stimuli

2010 ◽  
Vol 22 (2) ◽  
pp. 347-361 ◽  
Author(s):  
David V. Smith ◽  
Ben Davis ◽  
Kathy Niu ◽  
Eric W. Healy ◽  
Leonardo Bonilha ◽  
...  
Keyword(s):  
Spatial Attention ◽  
Visual Information ◽  
Brain Activation ◽  
Spatial Location ◽  
Auditory Stimuli ◽  
Activation Patterns ◽  
Central Target ◽  
Neuroimaging Study ◽  
Auditory Tasks ◽  
Selection Of

Neuroimaging studies suggest that a fronto-parietal network is activated when we expect visual information to appear at a specific spatial location. Here we examined whether a similar network is involved for auditory stimuli. We used sparse fMRI to infer brain activation while participants performed analogous visual and auditory tasks. On some trials, participants were asked to discriminate the elevation of a peripheral target. On other trials, participants made a nonspatial judgment. We contrasted trials where the participants expected a peripheral spatial target to those where they were cued to expect a central target. Crucially, our statistical analyses were based on trials where stimuli were anticipated but not presented, allowing us to directly infer perceptual orienting independent of perceptual processing. This is the first neuroimaging study to use an orthogonal-cuing paradigm (with cues predicting azimuth and responses involving elevation discrimination). This aspect of our paradigm is important, as behavioral cueing effects in audition are classically only observed when participants are asked to make spatial judgments. We observed similar fronto-parietal activation for both vision and audition. In a second experiment that controlled for stimulus properties and task difficulty, participants made spatial and temporal discriminations about musical instruments. We found that the pattern of brain activation for spatial selection of auditory stimuli was remarkably similar to what we found in our first experiment. Collectively, these results suggest that the neural mechanisms supporting spatial attention are largely similar across both visual and auditory modalities.

Evolving Model for Studying Driver-Vehicle System Performance in Longitudinal Control of Headway

1998 ◽  
Vol 1631 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Paul S. Fancher ◽  
Zevi Bareket
Keyword(s):  
Rate Of Change ◽  
Time Range ◽  
Longitudinal Control ◽  
Functional Relationships ◽  
Vehicle System ◽  
Range Rate ◽  
Evolving Model ◽  
Vehicle Dynamics Control ◽  
Parameter Values ◽  
Human Factors Research

A model for studying and evaluating the performance of drivers in controlling headway situations is currently being used to better understand how a driver’s perception of headway range and its rate of change in time (range rate) influence the performance of the driver-vehicle system in freeway driving situations. The model is based upon ideas derived from vehicle dynamics, control theory, and human factors research. It is an interpretive model in the sense that results obtained during real driving are processed to evaluate the parameter values and functional relationships used in the model. In this way, the model evolves as new data and information become available and as calculated results are interpreted and understood.

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