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Total results: 534

A Pilot Study on Biobehavioural Measurements on Air Traffic Controllers in Remote Tower Operations

Year: 2017

Authors: TJJ Bos, GDR Zon, E Füredi, D Dudas,D Rohács

What is the impact of shifting to remote tower operations on the Air Traffic Controller? In the joint HungaroControl-Netherlands Aerospace Centre NLR pilot project an assessment of biobehaviour on three air traffic controllers was made in a remote tower and conventional tower. The research is motivated by HungaroControl’s plans in shifting to remote tower operations at Budapest airport in the upcoming years. This pilot project is considered a feasibility study to investigate if an eye tracker and a heart rate sensor can be used to derive workload, the controllers’ division of attention over information elements, and scanning strategies in two such different environments. Given the limited number of participants and challenges in measuring workload in the two different operational environments conclusions, can only be drawn with care. Nevertheless, preliminary results suggest that there might be an increase in workload in the remote tower environment, and thus further research is needed to clarify at what extend Air Traffic Controllers’ workload could be different, what are the root causes of the increase and how that could be handled. Also, the pilot study has given confidence that useful biobehavioural measures can be obtained for comparison between the remote tower and the conventional tower, and to extend the research to a larger group of controllers.

Eye Tracking Glasses
Software

2 versions available

Aggregating physiological and eye tracking signals to predict perception in the absence of ground truth

Year: 2017

Authors: E Kasneci,T Kübler,K Broelemann

Today's driving assistance systems build on numerous sensors to provide assistance for specific tasks. In order to not patronize the driver, intensity and timing of critical responses by such systems is determined based on parameters derived from vehicle dynamics and scene recognition. However, to date, information on object perception by the driver is not considered by such systems. With advances in eye-tracking technology, a powerful tool to assess the driver's visual perception has become available, which, in many studies, has been integrated with physiological signals, i.e., galvanic skin response and EEG, for reliable prediction of object perception. We address the problem of aggregating binary signals from physiological sensors and eye tracking to predict a driver's visual perception of scene hazards. In the absence of ground truth, it is crucial to use an aggregation scheme that estimates the reliability of each signal source and thus reliably aggregates signals to predict whether an object has been perceived. To this end, we apply state-of-the-art methods for response aggregation on data obtained from simulated driving sessions with 30 subjects. Our results show that a probabilistic aggregation scheme on top of an Expectation-Maximization-based estimation of source reliabilities can predict hazard perception at a recall and precision of 96% in real-time.

Eye Tracking Glasses
Simulator

6 versions available

Analysis of a multimodal human-robot-interface in terms of mental workload

Year: 2017

Authors: M Schneider,B Deml

The trend away from highly automated processes using heavy industrial robots towards HRI-systems (human-robot-interaction) using light-weight robots, is leading to a strong increase concerning the technical complexity of future industrial work systems. This article reports the results of an experimental evaluation of a multimodal human-robot-interface. Two typical application scenarios from the robot programming were examined, each performed with three different modalities of control. The mental workload of the operators was operationalized by subjective, objective and physiological indicators. There were significant differences in mental workload between the different types of control in both application scenarios. The present results demonstrate the benefits of adaptive system design in human-robot-interaction.

Eye Tracking Glasses
Software

3 versions available

Analysis of potentials of an HMI-concept concerning conditional automated driving for system-inexperienced vs. system-experienced users

Year: 2017

Authors: K Bauerfeind, A Stephan, F Hartwich

Conditional automated driving (CAD) functions will be one of the key technologies promising comfort and efficiency in personal transportation. This work addresses the importance of a user-centered and variable Human-Machine-Interface (HMI) for CAD in consideration of different levels of trust. The question arises as to how the level of trust, presumably caused by system-experience with an automated system, modulates information needs. The variable HMI-concept was tested with a panel of 47 subjects in a driving simulator. Effects on system evaluation in terms of experience with a conditional automated system (between; system-inexperienced vs. system-experienced users) and the HMI (within; maximal-HMI with higher informational content vs. minimal-HMI with lower informational content) were examined. The gaze behaviour showed that the system-experienced users trusted the system more and monitored the system less frequently than the system-inexperienced users. System-experienced users focused on a non-driving-related task more often than system-inexperienced users. Even though, both user groups trusted the system more using the maximal-HMI than using the minimal-HMI, it is assumed, that long-term use will modulate the level of trust and the resulting information needs. This study supports the idea of adaptability of the HMI depending on the level of trust and the information needs.

Eye Tracking Glasses
Simulator

3 versions available

Assessing high cognitive load in drivers through electroencephalography

Year: 2017

Authors: D He, CC Liu, B Donmez

This paper explores the influence of high cognitive load on driver’s Electroencephalography (EEG) signals collected from four positions (TP9, Fp1, Fp2, TP10) along with other physiological signals, plus eye tracking, driving performance, and subjective measures. Although EEG has been used in driving research to assess mental workload, only a few studies focused on high cognitive load, but they utilized research-grade EEG systems. Recent advancements allow for less intrusive and more affordable systems to be incorporated into vehicles. We tested the feasibility of one such system to differentiate three incremental levels of cognitive taskload in a preliminary simulator study, which so far has been completed by 15 participants. Each participant completed a baseline drive with no secondary task and two drives with a modified version of the n-back task (1-back, 2-back). The modification removed the verbal response during auditory stimulus presentation to increase EEG signal quality, with the 2-back level still imposing higher cognitive demand than 1-back. The system tested was sensitive to taskload levels, with alpha band being sensitive among all difficulty levels; beta and gamma bands distinguishing 2-back level from the baseline and 1-back; and the delta band distinguishing baseline from the n-back levels. In line with previous studies, galvanic skin response and standard deviation of gaze position also showed significant stepwise trends from the baseline to 1-back and then to 2-back. Further research is needed to investigate the ability of consumer-grade EEG headbands to differentiate different driver states.

Eye Tracking Glasses
Simulator

3 versions available

Automating the process of gaze tracking data using soft clustering

Year: 2017

Authors: DV Jeevithashree, P Ray, P Natarajan

The aim of the paper is to automate the processing of gaze tracking data through soft clustering techniques. Standard analysis software for eye gaze tracking data requires users to define areas of interest, which may not be best option for exploratory analysis, where users may want to analyze eye gaze tracking data to know the area of interest. We have presented results on using Fuzzy c-means and Expectation Maximization algorithms on gaze tracking data and using an entropy based cluster validation index, we tried to automate identification of areas of interest. In our study, data from search task in digitally rendered 2D architectural plans have been explored and results indicated that irrespective of clustering technique, users fixated attention only 2 or 3 times for individual image. We have also presented GUI of a tool that can automatically identify areas of interest for any gaze tracking data sample using FCM or EM Algorithms.

Eye Tracking Glasses
Software

3 versions available

Calibme: Fast and unsupervised eye tracker calibration for gaze-based pervasive human-computer interaction

Year: 2017

Authors: T Santini,W Fuhl,E Kasneci

As devices around us become smart, our gaze is poised to become the next frontier of human-computer interaction (HCI). State-of-the-art mobile eye tracker systems typically rely on eye-model-based gaze estimation approaches, which do not require a calibration. However, such approaches require specialized hardware (e.g., multiple cameras and glint points), can be significantly affected by glasses, and, thus, are not fit for ubiquitous gaze-based HCI. In contrast, regression-based gaze estimations are straightforward approaches requiring solely one eye and one scene camera but necessitate a calibration. Therefore, a fast and accurate calibration is a key development to enable ubiquitous gaze-based HCI. In this paper, we introduce CalibMe, a novel method that exploits collection markers (automatically detected fiducial markers) to allow eye tracker users to gather a large array of calibration points, remove outliers, and automatically reserve evaluation points in a fast and unsupervised manner. The proposed approach is evaluated against a nine-point calibration method, which is typically used due to its relatively short calibration time and adequate accuracy. CalibMe reached a mean angular error of 0.59 (σ=0.23) in contrast to 0.82 (σ=0.15) for a nine-point calibration, attesting for the efficacy of the method. Moreover, users are able to calibrate the eye tracker anywhere and independently in ≤10 s using a cellphone to display the collection marker.

Eye Tracking Glasses
Software

2 versions available

Data Collection Report

Year: 2017

Authors: CC Liu

Driver distraction from secondary in-vehicle activities is recognized as a significant source of people injuries and fatalities on the road. Cognitive workload as one main source of diver distraction is vital to understand the driver state in partially automated cars. eDREAM Project, conducted during May 2015 to November 2016, was initiated to develop an advanced driver monitoring system that utilizes advanced sensory and vision technologies to improve driving experience and safety. Vehicle-based measures, physiological measures and video-based measures data were collected in order to discover the various impacts of cognitive load. Those measures were collected from a total of 36 gender-balanced participants and a driving simulator under three incremental cognitive task-load conditions. The NASA-TLX questionnaire was used for rating various demands and efforts in order to collect participants’ perceived cognitive workload level after each drive that contained different task-load. This document focused on the process of experiment design and implementation, future sections on resulted dataset and analysis results will be added.

Eye Tracking Glasses
Simulator

1 version available:

Design and development of a low-cost smartphone-based research platform for real-world driving studies

Year: 2017

Authors: M Nefzger

Naturalistic driving studies as a method to explore driving and driver behaviour in a natural environment have become increasingly popular in road safety research. However, data acquisition systems needed for these studies are expensive and require a profound technical expertise for the installation. This thesis reports on an alternative approach towards more affordable naturalistic driving studies – a smartphone-based system called Sensor Platform that leverages the phone’s sensors as well as external sensors to gather relevant driving data. In close cooperation with road safety experts, this project aimed to specify the requirements for such a system, develop a prototype, and evaluate from an user perspective as well as from a technical point of view. A focus group and an in-vehicle user study were conducted to gather the expert’s feedback. In order to judge the accuracy of Sensor Platform, a comparison to an industry-grade data acquisition system was performed on the real road. The analysis of the study data suggests that road safety experts like the high usability and value the time savings. Yet, in comparison to industry-grade data acquisition systems, Sensor Platform is not on par when it comes to data accuracy, mainly due to simpler filtering algorithms. All in all, the thesis adds to the knowledge of mobile data acquisition systems while also providing a basis for future road safety applications such as real-time interventions.

Eye Tracking Glasses
Software

2 versions available

Design of Filter-less Air Purifier by Using UI/UX Metrics

Year: 2017

Authors: JY Kim, DJ Kim,H Kim, JC Lee, YJ Lee

Objective: The aim of this study is to design an overall physical interface such as shape design, icons, and UI function of a filter-less air purifier with dust-collecting technology. Background: As a result of market research for the product, existing air purifier has not been able to solve the disadvantage of complexity of menu and noise and over-function. In addition, not only the function of the product but also the design has become an important factor of consumption. Method: This study was divided into research for the derivation of shape design concept and research for part of interior design. In the study for the design concept, we used the methodology based on the survey and quantification type 1 theory. For the interface design, we conducted icon preference test using the eye-tracker. Results: As a result of the quantification type 1 analysis, it was found that the rounded shape, top interface position, plastic texture, and penetrating shape of ventilation part were chosen to improve consumer’s feeling of healthy and fresh purifier. In the results of the eye-tracking experiment, the subjects selected the house and wave pattern icons with the air cleaning function, the LED on/off function icon selected, and the majority of participants selected the pest control icon. Conclusion: It is expected that Small and Medium enterprises would be able to improve their competitiveness by using UI/UX metrics.

Eye Tracking Glasses
Software

4 versions available