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Ergoneers VTK (Vehicle testing kit)

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Total results: 145

Tunnel safety: A pilot study investigating drivers’ fixation characteristics when approaching tunnel entrance at different driving speeds

Year: 2023

Authors: L Qin, DS Yang, YN Weng

This study presents the results of a driving experiment study on spatiotemporal characteristics of drivers’ fixation when entering a tunnel portal with different driving speeds. The study was performed during the daytime in a relatively long tunnel. Six experienced drivers were recruited to participate in the driving experiment. Experimental data of pupil area and fixation point position (from 200 m before the tunnel to the tunnel portal) were collected by non-intrusive eye-tracking equipment for three predetermined vehicle speeds (40 km/h, 60 km/h and 80 km/h). Fixation maps (color-coded maps showing distributed data) were created from fixation point position data to quantify visual behaviour changes. The results demonstrated that vehicle speed has a significant impact on pupil area and fixation zones. Fixation area and average pupil area had a significant negative correlation with vehicle speed during the daytime. Moreover, drivers concentrated more on the tunnel entrance portal, front road pavement and car control wheeling. The results revealed that the relationship between pupil area and vehicle speed fitted an exponential function. Limitations and future directions of the study are also discussed.

Eye Tracking Glasses
Simulator

2 versions available

Vehicle Braking Performance and Saccadic Eye Movement with Different Illuminance Transmission Exposures in Digital Driving Simulation

Year: 2023

Authors: A Ahmad,SA Rosli,AH Chen

During driving, the eye moves as we shift the focus of our eye from one point of interest to another point, known as saccadic eye movement. Although the eye movement is not affected under different illuminance conditions during driving, the movement is involved in the ability to drive. This study investigates the correlation between saccadic eye movement and vehicle braking performance when the illuminance transmission was reduced by introducing a neutral density filter in front of the eyes. This is conducted by exposing four levels of illuminance transmission which are 100%, 50%, 30%, and 15% with driving simulation as braking performance is measured. Based on the baseline data from our preceding saccadic investigation on the same subjects using the Dikablis eye tracker, the braking performance is analyzed together with the eye movement data. Twenty-eight young adults with proper license and driving experience, as well as a good history of systemic, ocular, and binocular vision health, are involved in this study. The driving task is conducted via driving simulation, with the subjects instructed to drive naturally. There is no significant correlation between the number of saccadic eye movements and all investigated vehicle braking performances (speed, time, and length) under reduced illuminance transmissions of 30% and 15% (p>0.05). While our previous investigation reveals that the saccadic eye movement is not affected by different illuminance transmissions when driving, this current study concludes that the vehicle braking performance is not correlated with the saccades while driving under those low illuminance exposures.

Eye Tracking Glasses
Simulator

1 version available:

Analyzing the influencing factors and workload variation of takeover behavior in semi-autonomous vehicles

Year: 2022

Authors: H Zhang, Y Zhang, Y Xiao, C Wu

There are many factors that will influence the workload of drivers during autonomous driving. To examine the correlation between different factors and the workload of drivers, the influence of different factors on the workload variations is investigated from subjective and objective viewpoints. Thirty-seven drivers were recruited to participant the semi-autonomous driving experiments, and the drivers were required to complete different NDRTs (Non-Driving-Related Tasks): mistake finding, chatting, texting, and monitoring when the vehicle is in autonomous mode. Then, we introduced collision warning to signal there is risk ahead, and the warning signal was triggered at different TB (Time Budget)s before the risk, at which time the driver had to take over the driving task. During driving, the NASA-TLX-scale data were obtained to analyze the variation of the driver’s subjective workload. The driver’s pupil-diameter data acquired by the eye tracker from 100 s before the TOR (Take-Over Request) to 19 s after the takeover were obtained as well. The sliding time window was set to process the pupil-diameter data, and the 119-s normalized average pupil-diameter data under different NDRTs were fitted and modeled to analyze the variation of the driver’s objective workload. The results show that the total subjective workload score under the influence of different factors is as follows: obstacle-avoidance scene > lane-keeping scene; TB = 7 s and TB = 3 s have no significant difference; and mistake finding > chatting > texting > monitoring. The results of pupil-diameter data under different factors are as follows: obstacle-avoidance scene > lane-keeping scene; TB = 7 s > TB = 3 s; and monitoring type (chatting and monitoring) > texting type (mistake finding and texting). The research results can provide a reference for takeover safety prediction modeling based on workload.

Eye Tracking Glasses
Simulator

13 versions available

Classification of driver cognitive load: Exploring the benefits of fusing eye-tracking and physiological measures

Year: 2022

Authors: D He, Z Wang,EB Khalil,B Donmez

In-vehicle infotainment systems can increase cognitive load and impair driving performance. These effects can be alleviated through interfaces that can assess cognitive load and adapt accordingly. Eye-tracking and physiological measures that are sensitive to cognitive load, such as pupil diameter, gaze dispersion, heart rate (HR), and galvanic skin response (GSR), can enable cognitive load estimation. The advancement in cost-effective and nonintrusive sensors in wearable devices provides an opportunity to enhance driver state detection by fusing eye-tracking and physiological measures. As a preliminary investigation of the added benefits of utilizing physiological data along with eye-tracking data in driver cognitive load detection, this paper explores the performance of several machine learning models in classifying three levels of cognitive load imposed on 33 drivers in a driving simulator study: no external load, lower difficulty 1-back task, and higher difficulty 2-back task. We built five machine learning models, including k-nearest neighbor, support vector machine, feedforward neural network, recurrent neural network, and random forest (RF) on (1) eye-tracking data only, (2) HR and GSR, (3) eye-tracking and HR, (4) eye-tracking and GSR, and (5) eye-tracking, HR, and GSR. Although physiological data provided 1%–15% lower classification accuracies compared with eye-tracking data, adding physiological data to eye-tracking data increased model accuracies, with an RF classifier achieving 97.8% accuracy. GSR led to a larger boost in accuracy (29.3%) over HR (17.9%), with the combination of the two factors boosting accuracy by 34.5%. Overall, utilizing both physiological and eye-tracking measures shows promise for driver state detection applications.

Eye Tracking Glasses
Simulator

7 versions available

Does gender affect the driving performance of young patients with diabetes?

Year: 2022

Authors: s

Recent evidence suggests that poor glycemic control among young patients with type 1 diabetes mellitus (T1DM) has negative cognitive and physical effects, whose extent is gender-dependent. For example, female patients with diabetes present more physical and cognitive limitations than male patients in terms of cognitive adjustment, quality of decision making, and functioning. Studies about traffic safety report that diabetic drivers are at increased risk of being involved in road crashes, especially when driving in a state of hypoglycemia under which their blood glucose level is too low. We have recently demonstrated that acute hyperglycemia (when the blood glucose level is too high) can also lead to poor driving performance among T1DM young adult patients. Against this background, the objective of the present study was to find out whether gender affects the driving performance of young drivers with diabetes. Twenty-six T1DM drivers participated in a counterbalanced crossover experiment. While being monitored by an eye tracker, they drove a driving simulator and twice navigated through the nine hazardous scenarios: once under a normal blood glucose (euglycemia) level and once high blood glucose (hyperglycemia) level. The first main result is that young female drivers are more affected by diabetes than young male drivers, regardless of momentary glycemic changes. The second main result is that poor glycemic control substantially deteriorates hazard perception and driving performance of young males with diabetes. Thus, it is argued that an uncontrolled state of a high blood glucose level may be more hazardous for young males with diabetes since it negatively impacts their driving performance.

Eye Tracking Glasses
Simulator

7 versions available

Evaluation of a dynamic blocking concept to mitigate driver distraction: three simulator studies

Year: 2022

Authors: J Leipnitz, A Gross, J Dostert, T Baumgarten

In recent years, the number and complexity of in-vehicle infotainment systems has been steadily increasing. While these systems certainly improve the driving experience, they also increase the risk for driver distraction. International standards and guidelines provide methods of measuring this distraction along with test criteria that help automakers decide whether an interface task is too distracting to be used while driving. Any specific function failing this test should therefore be locked out for use by the driver. This study implemented and tested a dynamic approach to this blocking by algorithmically reacting to driver inputs and the pace of the interaction in order to prevent drivers from having prolonged or too intense sequences of in-vehicle interactions not directly related to driving. Three simulated driving experiments in Germany and the United States were conducted to evaluate this dynamic function blocking concept and also cater for differences in the status quo of either no blocking or static blocking. The experiments consisted of a car following scenario with various secondary interface tasks and always included a baseline condition where no blocking occurred as well as an implementation of the dynamic function blocking. While Experiments 1 and 3 were aimed at collecting and analyzing gaze and driving data from more than 20 participants, Experiment 2 focused on the user experience evaluation of different visual feedback implementations from 13 participants. The user experience as rated by these participants increased throughout the course of all three studies and helped further improve both the concept and feedback design. In the experiments the total glance time towards the road was significantly higher in the dynamic function blocking condition compared to the baseline, already accounting for the increase in total task time inherent to the dynamic condition. Participants developed two strategies of interacting with the dynamic function blocking. They either operated at their normal baseline speed and incurred task blockings or operated slower to avoid the blockings. In the latter strategy, participants chunked their interactions into smaller steps with the present data suggesting that they used the pauses in between chunks to look back onto the road ahead. Theoretical and practical implications of this first evaluation of a dynamic function blocking concept are discussed.

Simulator
Software

6 versions available

Evaluation of the optimal quantity of in-vehicle information icons using a fuzzy synthetic evaluation model in a driving simulator

Year: 2022

Authors: J Chen, X Wang, Z Cheng, Y Gao

In-Vehicle Information (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers. The interface design, especially the quantity of icons presented to the driver such as those for navigation, music, and phone calls, has not been fully researched. To determine the optimal number of icons, a systematic evaluation of the IVI Human Machine Interface (HMI) was examined using single-factor and multivariate analytical methods in a driving simulator. When one-way ANOVA was performed, the results showed that the 3-icon design scored best in subjective driver assessment, and the 4-icon design was best in the steering wheel angle. However, when a new method of analyzing the data that enabled a simultaneous accounting of changes observed in the dependent measures, 3 icons had the highest score (that is, revealed the overall best performance). This method is referred to as the fuzzy synthetic evaluation model (FSE). It represents the first use of it in an assessment of the HMI design of IVI. The findings also suggest that FSE will be applicable to various other HMI design problems.

Simulator
Software

4 versions available

How users of automated vehicles benefit from predictive ambient light displays

Year: 2022

Authors: T Hecht, S Weng, LF Kick,K Bengler

With the introduction of Level 3 and 4 automated driving, the engagement in a variety of non-driving related activities (NDRAs) will become legal. Previous research has shown that users desire information about the remaining time in automated driving mode and system status information to plan and terminate their activity engagement. In past studies, however, the positive effect of this additional information was realized when it was integrated in or displayed close by the NDRA. As future activities and corresponding items will be diverse, a device-independent and non-interruptive way of communication is required to continuously keep the user informed, thus avoiding negative effects on driver comfort and safety. With a set of two driving simulator studies, we have investigated the effectiveness of ambient light display (ALD) concepts communicating remaining time and system status when engaged in visually distracting NDRAs. In the first study with 21 participants, a traffic light color-coded ALD concept (LED stripe positioned at the bottom of the windshield) was compared to a baseline concept in two subsequent drives. Subjects were asked to rate usability, workload, trust, and their use of travel time after each drive. Furthermore, gaze data and NDRA disengagement timing was analyzed. The ALD with three discrete time steps led to improved usability ratings and lower workload levels compared to the baseline interface without any ALD. No significant effects on trust, attention ratio, travel time evaluation, and NDRA continuation were found, but a vast majority favored the ALD. Due to this positive evaluation, the traffic light ALD concept was subsequently improved and compared to an elapsing concept in a subsequent study with 32 participants. In addition to the first study, the focus was on the intuitiveness of the developed concepts. In a similar setting, results revealed no significant differences between the ALD concepts in subjective ratings (workload, usability, trust, travel time ratings), but advantages of the traffic light concept can be found in terms of its intuitiveness and the level of support experienced.

Eye Tracking Glasses
Simulator

7 versions available

Interaction strategies with advanced driver assistance systems

Year: 2022

Authors: N Neuhuber,P Pretto,B Kubicek

When using advanced driver assistance systems (ADAS) drivers need to calibrate their level of trust and interaction strategy to changes in the driving context and possible consequent reduction of system reliability (e.g. in harsh weather conditions). By investigating and identifying categories of drivers who choose inadequate interaction strategies, it is possible to address unsafe usage with e.g. tutoring lessons tailored to the respective driver category. This paper presents two studies investigating categories of drivers who apply different interaction strategies when using ADAS. Study I was designed as an exploratory field study with 37 participants interacting with a SAE level 2 system. For the exploratory study, it was important to observe and understand the interaction strategies in a driving context which entails the real complexity of the driving task. The experimental set-up of study II (simulator study), however, allowed to clearly interpret the interaction strategies as either calibrated or un-calibrated by varying the situational risk. Participants (N = 33) were driving in a situation where the system was either working reliably (low-risk condition) or in a situation where the system displayed repeatedly errors under harsh weather conditions (high-risk condition). Cluster analyses with the variables trust, monitoring behavior towards the system and usage behavior were performed to analyze potential categories of drivers. Extreme driver categories with interaction strategies indicative for both misuse and disuse were observed in both studies. In study I, drivers were categorized as either highly trusting attentive, moderately trusting attentive, moderately inattentive, inattentive or skeptical. In study II, drivers were categorized as either un-calibrated, calibrated, inconsistent or skeptical. Taken together, results underline the need of tutoring systems that are tailored for different driver categories.

Eye Tracking Glasses
Simulator

5 versions available

Interruption management in the context of take-over-requests in conditional driving automation

Year: 2022

Authors: A Borowsky,N Zangi

Drivers of partially automated vehicles are relieved from parts of the driving tasks allocated to the automated driver. This reduction in driving demands encourages them to engage with nondriving related tasks, which may impair awareness of the road environment once a takeover request (TOR) is initiated. This article examined the four suggested strategies drivers that take to regain control following a TOR, from the perspective of interruption management principles. Thirty students participated in a simulated study of two drives, where we manipulated TOR alerts, time to regain control, and potential road hazards. We hypothesized that all four interruption management strategies will be observed. Our hypothesis was confirmed. Four strategies were identified. Most drivers chose strategy 2 to accept and initiate the takeover immediately after the TOR started. The second frequent strategy was to reject the TOR but look at the road. Drivers’ strategy choices changed following alert type and the chronological drive order. With simulated driving experience (i.e., second drive), drivers postponed taking control, adapting to the time budget. Yet, inaccurate understanding of the situation or over-trust affected the chosen strategy. We conclude that interruption management principles are beneficial for studying how drivers respond to TORs and evaluating options to improve TOR performance.

Eye Tracking Glasses
Simulator

2 versions available