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Total results: 642

Some on-road glances are more equal than others: Measuring engagement in the driving task

Year: 2019

Authors: L Hoekstra

The current work examines a methodology developed for assessing driver attention management using high-precision eye glances towards safety-relevant driving information. The Task Analysis Eye Movement Overlay (TAEMO) method uses task analyses, video recordings of a driving scenario, and eye glance data toward visual keys that drivers sample during the driving scenario to directly measure driver engagement. This methodology has applications for evaluating infrastructure design, driver impairment assessment, driver training, driver distraction research, and vehicle human-machine interface (HMI) system design.

3 versions available

The effect of partial automation on driver attention: A naturalistic driving study

Year: 2019

Authors: J Gaspar,C Carney

Objective: This naturalistic driving study investigated how drivers deploy visual attention in a partially automated vehicle. Background: Vehicle automation is rapidly increasing across vehicle fleets. This increase in automation will likely have both positive and negative consequences as drivers learn to use the new technology. Research is needed to understand how drivers interact with partially automated vehicle systems and what impact new technology has on driver attention. Method: Ten participants drove a Tesla Model S for 1 week during their daily commute on a stretch of busy interstate. Drivers were instructed to use Autopilot, a system that provides both lateral and longitudinal control, as much as they felt comfortable while driving on the interstate. Driver-facing video data were recorded and manually reduced to examine glance behavior. Results: Drivers primarily allocated their visual attention between the forward roadway (74% of glance time) and the instrument panel (13%). With partial automation engaged, drivers made longer single glances and had longer maximum total-eyes-off-road time (TEORT) associated with a glance cluster. Conclusion: These results provide a window into the nature of visual attention while driving with partial vehicle automation. The results suggest that drivers may be more willing to execute long, “outlier” glances and clusters of glances to off-road locations with partial automation. The findings highlight several important human factors considerations for partially automated vehicles.

7 versions available

The influence of a gaze direction based attention request to maintain mode awareness

Year: 2019

Authors: C Kurpiers, D Lechner, F Raisch

Future vehicles will combine different levels of driving automation characterized by varying responsibilities for users. This development will intensify system complexity which poses the risk of confusing the driver. We hypothesize that the users’ mode awareness suffers especially when changing from Level 3 “Conditional Automation” to Level 2 “Partial Automation”. Therefore, automated systems need to be designed in a way that minimizes confusion with regard to the automation mode. The article describes the influence of a gaze direction based Attention Request (ATR) to avoid mode confusion with the aim of contributing to the reliable operation of different levels of automation in one vehicle. Two similar studies were conducted. One took place in a dynamic driving simulator with 40 participants. Every participant drove for 10 minutes with a partially automated driving (PAD) (SAE level 2) system and conditionally automated driving (CAD) (SAE level 3) system in the order PAD/CAD/PAD. The second study was conducted on a German highway in a Wizard-of-Oz car. All 40 test persons drove in each PAD and CAD phase 8 minutes in the order of PAD/CAD/PAD/CAD/PAD/CAD. The CAD-system was in both studies a high performing Hands-Off Level 2 system that required no input of the driver. To promote the same mental model for all participants as it is a requirement to measure the differences in mode awareness, all persons became a detailed description of the Level 2 and 3 systems presented by video and text. Both studies used a between-subject-design to measure the influence of an ATR. The ATR was based on the gaze direction of the driver and initiated by the investigator when the drivers gaze was not in the street AOI for longer than 4 seconds. Mode awareness was operationalized by the visual attention towards driving-relevant areas, a qualitative analysis of a questionnaire and followed by an interview. The ATR was proven to be an effective action to maintain the mode awareness by using a level 2 and 3 system within one car. Specifically, the visual attention did not decrease by an intermitted CAD drive during PAD. Moreover, the visual attention to the road scene increased for the group with an ATR during PAD. This was indicated by the measurement of a significant interaction effect for the development of the visual attention to the road scene for the groups with and without ATR. Thus, the gaze direction-based ATR was proven to be an effective measure to maintain mode awareness, if different levels of automation are combined in one vehicle. This result helps to take the next step for realizing such combined multilevel systems with tailored HMIs for advanced driver assistance systems. Moreover, it has to be considered, that the studies put the emphasis on the first glance of the drivers, during their first contact with partly and conditionally automated systems. Further studies should investigate the long term effect of an ATR.

2 versions available

TobiiGlassesPySuite: An open-source suite for using the Tobii Pro Glasses 2 in eye-tracking studies

Year: 2019

Authors: D De Tommaso,A Wykowska

In this paper we present the TobiiGlassesPySuite, an open-source suite we implemented for using the Tobii Pro Glasses 2 wearable eye-tracker in custom eye-tracking studies. We provide a platform-independent solution for controlling the device and for managing the recordings. The software consists of Python modules, integrated into a single package, accompanied by sample scripts and recordings. The proposed solution aims at providing additional methods with respect to the manufacturer's software, for allowing the users to exploit more the device's capabilities and the existing software. Our suite is available for download from the repository indicated in the paper and usable according to the terms of the GNU GPL v3.0 license.

3 versions available

Trust in highly automated driving

Year: 2019

Authors: A Stephan

The automotive industry is on the verge of a new technology: self-driving vehicles. Such highly automated driving vehicles are more and more technically feasible, and corporations and research institutes all over the world are investing time and money to bring the once futuristic vision on the road. The technology is developed with the goal to release the driver from the manual task of controlling the vehicle. Through that, it shall increase driving comfort and, above all, contribute to the enhancement of overall road safety. Beyond further technical development, psychological aspects and the creation of an optimal user experience gain importance for highly automated driving functionality. In particular, trust in this kind of functionality has yet to be built up for future societal usage. Otherwise, if people are not willing to entrust control to such a vehicle, it will not be used and the potential of highly automated driving cannot be fully exploited. The aim of this work is to identify influential factors on trust in highly automated driving vehicles and to examine how this trust can be supported by a specific human-machine interface (HMI). To this end, three main studies were conducted with participants. Different HMI concepts were tested in these user studies in a prototype vehicle on public roads as well as in a simulated environment. The aim of the first real-driving study (N = 28) with the highly automated driving vehicle was to test influential factors on trust in such a vehicle. The personality characteristic desire for control as well as a general attitude towards technology were identified as relevant factors. However, most important for trust was the perceived performance of the system. In the second user study (N = 72), the influence of system boundaries on trust was examined with the help of a simulated environment. It was proven that the type of the experienced system limit plays a crucial role. In particular, the non-detection of a relevant event within the driving situation diminished trust, while a false detection led to little trust reduction. Over several trial days, it was examined in a third user study (N = 18) how trust develops beyond a first contact with a highly automated driving system. In this real-driving study, first indications were found that the relevance of the HMI increases with prolonged system use. A trust model set up based on previous insights and theories was transferred to the new context of highly automated driving with the help of these studies. Furthermore, guidelines for the design of an HMI concept for highly automated vehicles were collected and applied. Thereby, the insights of this work support developers in designing HMI concepts to promote trust in automated driving functionality. Even if the future driver no longer needs to take over driving tasks, it is recommended to provide an adequate HMI concept supporting trust development.

3 versions available

Using gaze-based interactions in automated vehicles for increased road safety

Year: 2019

Authors: H Schmidt,G Zimmermann,A Schmidt

The development of self-driving vehicles seems to go well with the growing demand for the daily use of mobile devices. However, autonomous vehicles will still need manual intervention in unforeseen or dangerous situations. Therefore, it is important for the driver to stay aware of the traffic situation around, and so to be quickly able to take over. We developed a prototype which represents media content on a simulated windshield display and uses gaze tracking as an additional form of input device for the driver. Although we intentionally pull away the driver's gaze from the driving situation, this seems to be less of a distraction than using hand-held mobile devices or dash-integrated display devices. We hypothesize that the time to regain control with our prototype is shorter compared to traditional media presentation. This work-in-progress paper provides insight to the concept of the prototype while first results will be presented at the conference.

1 version available:

Visual attention failures towards vulnerable road users at intersections: Results from on-road studies

Year: 2019

Authors: NE Kaya

This dissertation investigates the visual attention failures of drivers towards vulnerable road users (VRUs) at intersections. VRUs include pedestrians, cyclists, and motorcyclists. This research uses on-road studies to observe driver behavior in real-world settings. The findings reveal that drivers often fail to notice VRUs at intersections, leading to potential collisions. By identifying the specific circumstances and conditions under which these failures occur, this work aims to improve intersection safety and inform the design of interventions to enhance driver awareness of VRUs.

4 versions available

Visualizing natural language interaction for conversational in-vehicle information systems to minimize driver distraction

Year: 2019

Authors: M Braun,N Broy,B Pfleging,F Alt

In this paper we investigate how natural language interfaces can be integrated with cars in a way such that their influence on driving performance is being minimized. In particular, we focus on how speech-based interaction can be supported through a visualization of the conversation. Our work is motivated by the fact that speech interfaces (like Alexa, Siri, Cortana, etc.) are increasingly finding their way into our everyday life. We expect such interfaces to become commonplace in vehicles in the future. Cars are a challenging environment, since speech interaction here is a secondary task that should not negatively affect the primary task, that is driving. At the outset of our work, we identify the design space for such interfaces. We then compare different visualization concepts in a driving simulator study with 64 participants. Our results yield that (1) text summaries support drivers in recalling information and enhances user experience but can also increase distraction, (2) the use of keywords minimizes cognitive load and influence on driving performance, and (3) the use of icons increases the attractiveness of the interface.

14 versions available

Work, aging, mental fatigue, and eye movement dynamics

Year: 2019

Authors: RZ Marandi

Mental load and fatigue are important multidimensional phenomena concerning increasing involvement of elderly individuals in computer work. Fatigue may be associated with reduced cognitive resources and increased errors. Micro-breaks are strategic solutions to impede fatigue subject to design constraints, such as a timing plan. The present work aimed to use eye tracking as a promising technology to measure mental load and fatigue in young and elderly adults (Studies I and II), and to apply micro-breaks based on fatigue-related changes in eye movements to decelerate fatigue development (Study III). The three studies involved 58 young and elderly participants. A novel task resembling computer work was developed to induce mental load (Study I). Gaze positions and pupillary responses were recorded during the task execution to detect ocular events (saccades, fixations, and blinks) and to quantify their characteristics as oculometrics. In Study I, the task was performed with three load levels across two days. In addition to measuring the load effects on performance, perceived workload, and oculometrics, the test-retest reliability of 19 oculometrics was assessed. In Study II, the effect of 40-min time-on-task was explored on oculometrics, perceived fatigue, and performance. Then, in Study III, a predictive model of fatigue was developed based on the data collected in Study II. Oculometrics-based biofeedback was implemented in real time to detect fatigue using the developed model, which triggered micro-breaks upon fatigue detection to impede it. Perceived fatigue and workload were compared between a session with the biofeedback and a control session with self-triggering micro-breaks. A set of oculometrics were found to reflect mental load (Study I) and fatigue (Study II) in both age groups. Similar trends in oculometrics were observed with increased mental load and fatigue, implying shared neural systems for both conditions (Studies I and II). Age-related differences were exhibited in a few of the oculometrics (Study II), but age as a feature did not significantly contribute to fatigue detection (Study III). The biofeedback reduced workload and fatigue development, which suggests an improved strategy to design the timing plan of micro-breaks (Study III). All in all, the findings may support the viability of detecting the effects of fatigue and mental load on oculometrics to apply oculometrics-based biofeedback in computer work.

8 versions available

A novel method for estimating free space 3D point-of-regard using pupillary reflex and line-of-sight convergence points

Year: 2018

Authors: Z Wan, X Wang, K Zhou, X Chen, X Wang

In this paper, a novel 3D gaze estimation method for a wearable gaze tracking device is proposed. This method is based on the pupillary accommodation reflex of human vision. Firstly, a 3D gaze measurement model is built. By uniting the line-of-sight convergence point and the size of the pupil, this model can be used to measure the 3D Point-of-Regard in free space. Secondly, a gaze tracking device is described. By using four cameras and semi-transparent mirrors, the gaze tracking device can accurately extract the spatial coordinates of the pupil and eye corner of the human eye from images. Thirdly, a simple calibration process of the measuring system is proposed. This method can be sketched as follows: (1) each eye is imaged by a pair of binocular stereo cameras, and the setting of semi-transparent mirrors can support a better field of view; (2) the spatial coordinates of the pupil center and the inner corner of the eye in the images of the stereo cameras are extracted, and the pupil size is calculated with the features of the gaze estimation method; (3) the pupil size and the line-of-sight convergence point when watching the calibration target at different distances are computed, and the parameters of the gaze estimation model are determined. Fourthly, an algorithm for searching the line-of-sight convergence point is proposed, and the 3D Point-of-Regard is estimated by using the obtained line-of-sight measurement model. Three groups of experiments were conducted to prove the effectiveness of the proposed method. This approach enables people to obtain the spatial coordinates of the Point-of-Regard in free space, which has great potential in the application of wearable devices.

10 versions available