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Total results: 232

Drivers’ visual characteristics in small-radius optically long tunnels on rural roads

Year: 2021

Authors: S Wang, Z Du, G Chen, H Zheng, Z Tang

This study aims to investigate drivers’ visual characteristics under different radii and turning conditions in small-radius optically long tunnels on rural roads. Fixation and saccade were our main research objectives. We conducted real vehicle tests in optically long tunnels under four different radii. Using the distribution of gaze points, fixation duration, and fixation frequency, the drivers’ fixation characteristics were examined. In addition, the drivers’ saccade characteristics were examined by selecting the saccade duration, saccade frequency, and saccade amplitude. Accordingly, we established mathematical models of fixation duration and saccade duration with a radius under different turning conditions in different zones. Along with the visual task, we further examined drivers’ characteristics in optically long tunnels. We found that the smaller the tunnel radius, the more focused gaze points on inside of the curves, the larger the fixation duration, and the lower the safety with higher psychological pressure. In the zone where the exit portal was invisible, drivers’ tension and risk were higher during turning right, whereas drivers’ tension and risk were higher during turning left in the zone that the exit portal was visible.

Eye Tracking Glasses
Simulator

2 versions available

Drivers’ Visual Characteristics of Urban Expressway Based on Eye Tracker

Year: 2021

Authors: T Feng, Z Zhao, X Tian

In order to compare and analyze the visual characteristics of drivers in the congested and unblocked state of urban expressways, real vehicle tests were carried out on the eastern expressway in Changchun City using the German Dikablis eye tracker and its supportingD-Lab software. The test data was processed by using descriptive statistical analysis and non-parametric inspection methods to quantify the impact of congestion on the driver’s visual characteristics. The results show that drivers mainly obtain traffic information by gaze when driving on the expressway, and the gaze points are mostly concentrated on the road vehicles; the driver’s gaze duration and scan duration in the congested state account for the highest proportions in the 200–250 ms and 0–25 ms time periods, respectively; the average gaze duration and the average scan duration of the drivers in the congested state were higher than those in the unblocked state. The driver's gaze duration and saccade duration in the two states are significantly different, and the Mann–Whitney U test results are less than 0.05; the pupil area changes more drastically in the congested state, and the pupil area change rate is 38.67%.

Eye Tracking Glasses
Software

4 versions available

Evaluating the effects of in-vehicle side-view display layout design on physical demands of driving

Year: 2021

Authors: D Beck,J Jung, W Park

Objective: A driving simulator study was conducted to comparatively evaluate the effects of three camera monitor system (CMS) display layouts and the traditional side-view mirror arrangement on the physical demands of driving. Background: Despite the possible benefits of CMS displays in reducing the physical demands of driving, little empirical evidence is available to substantiate these benefits. The effects of CMS display layout designs are not well understood. Method: The three CMS display layouts varied in the locations of the side-view displays: (A) inside the car near the conventional side-view mirrors, (B) on the dashboard at each side of the steering wheel, and (C) on the center fascia with the displays joined side by side. Twenty-two participants performed a safety-critical lane changing task with each design alternative. The dependent measures were the following: spread of eye movement, spread of head movement, and perceived physical demand. Results: Compared with the traditional mirror system, all three CMS display layouts showed a reduction in physical demands, albeit differing in the types/magnitudes of physical demand reduction. Conclusion: Well-designed CMS display layouts could significantly reduce the physical demands of driving. The physical demands were reduced by placing the CMS displays close to the position of the driver’s normal line-of-sight when looking at the road ahead and locating each CMS display on each side of the driver, that is, at locations compatible with the driver’s expectation. Application: Physical demand reductions by CMS displays would especially benefit drivers frequently checking the side-view mirrors with large eye/head movements and physically weak/impaired drivers.

Eye Tracking Glasses
Simulator

9 versions available

Evaluating the impacts of driver’s pre-warning cognitive state on takeover performance under conditional automation

Year: 2021

Authors: S Agrawal,S Peeta

To design better fallback procedures and enhance road safety for conditionally automated vehicles (SAE Level 3), it is important to understand the factors that affect driver’s takeover performance (i.e., driving performance while resuming manual control). This study investigates the impacts of driver’s pre-warning cognitive state (i.e., before the issuance of a takeover warning) on takeover performance. Most existing studies assess takeover performance by independently analyzing driving performance indicators (e.g., minimum time-to-collision and maximum deceleration), and thereby ignore their associated interdependencies. This study proposes a novel comprehensive takeover performance metric, Takeover Performance Index (TOPI), that combines multiple driving performance indicators representing three aspects of takeover performance: risk of collision, the intensity of the driver’s response, and trajectory quality. Further, the driver’s pre-warning cognitive state is estimated by analyzing neurophysiological data (i.e., brain electrical activity) measured using an electroencephalogram (EEG) for 118 participants in driving simulator experiments. Linear mixed models are estimated for takeover performance to analyze its linkages to the driver’s pre-warning cognitive state, novelty in takeover experience (i.e., prior experience with a takeover situation), type of takeover warning (i.e., non-mandatory takeover vs. mandatory takeover), age, and driving experience. In this study, most drivers intervened in non-mandatory takeover scenarios and exhibited poor takeover performance. We observed three crashes across 287 runs. The study results show that takeover performance decreases with age but increases with driving experience when the driver is under certain pre-warning cognitive states, including fatigue, drowsiness, passive attention, and low level of alertness. They also illustrate that the novelty in takeover experience and mandatory takeover warning negatively affects takeover performance. The study findings provide insights for developing operator training and licensing strategies, designing regulations for the use of automated vehicles, and factoring driver cognition in designing fallback procedures in automated vehicles.

Eye Tracking Glasses
Simulator

5 versions available

Evaluating the impacts of situational awareness and mental stress on takeover performance under conditional automation

Year: 2021

Authors: S Agrawal,S Peeta

Several safety concerns emerge for the transition of control from the automated driving system to a human driver after the vehicle issues a takeover warning under conditional vehicle automation (SAE Level 3). In this context, recent advances in in-vehicle driver monitoring systems enable tracking drivers’ physiological indicators (e.g., eye-tracking and heart rate (HR) measures) to assess their real-time situational awareness (SA) and mental stress. This study seeks to analyze differences in driver’s SA and mental stress over time (i.e., successive experiment runs) using these physiological indicators to assess their impacts on takeover performance. We use eye-tracking measures (i.e., on-road glance rate and road attention ratio) as indicators of driver’s SA during automated driving. Further, we use the pre-warning normalized HR (NHR) and HR variability (HRV) as well as the change in NHR and HRV after the takeover warning as indicators of mental stress immediately before and the change in mental stress after the takeover warning, respectively. To analyze the effects of driver state (in terms of SA and mental stress) on the overall takeover performance, this study uses a comprehensive metric, Takeover Performance Index (TOPI), proposed in our previous work (Agrawal & Peeta, 2021). The TOPI combines multiple driving performance indicators while partly accounting for their interdependencies. Results from statistical analyses of data from 134 participants using driving simulator experiments illustrate significant differences in driver state over successive experiment runs, except for the change in mental stress after the takeover warning. Some significant correlations were found between the physiological indicators of SA and mental stress used in this study. Takeover performance model results illustrate a significant negative effect of change in NHR after the takeover warning on the TOPI. However, none of the other physiological indicators show significant impacts on takeover performance. The study findings provide valuable insights to auto manufacturers for designing integrated in-vehicle driver monitoring and warning systems that enhance road safety and user experience.

Eye Tracking Glasses
Simulator

7 versions available

Extended Evaluation of Training Programs to Accelerate Hazard Anticipation Skills in Novice Teens Drivers

Year: 2021

Authors: EE O'Neal

The objective of this research effort was to evaluate two driver training programs by examining young driver performance and eye movements in a driving simulator. Training program content was assessed and potential hazards were selected across both programs for inclusion in the simulator drives. These were implemented as potential hazards that did not manifest. Each study drive included the same number and types of driving situations, though the order of appearance and scenery details varied by study drive. Teens ages 15 and 16 completed a baseline study drive within two weeks of obtaining a license allowing them to drive independently without a supervisor in the vehicle. Participants were randomly assigned to one of the training conditions or to control (no training). Those assigned to training completed the respective program immediately after the baseline study drive. Participants completed a second study drive after six weeks of independent driving experience. Funding from the SAFER-SIM UTC to conduct an extended evaluation supported a third study drive that occurred after approximately 24 weeks of independent driving. At each visit, participants completed a different version of the study drive. During all study drives, participants wore a head-mounted eye tracker and simulator driving performance was recorded. Eye movement data was manually coded for a select set of driving events. In addition, the eye and simulator data were combined for three events to create a composite measure based on Endsley’s model of situation awareness [1, 2]. Generally, the analysis of driver attention and driving mitigation of potential hazards revealed few significant differences among the training and control conditions. Among the significant findings observed for ACCEL, there seemed to be a positive impact with respect to hazard anticipation and mitigation. However, ACCEL was not found to improve attention maintenance relative to control during a phone dialing task. The significant results for PALM training suggested it may be effective at helping novice drivers identify, monitor, and respond to potential hazards, especially for those hazards directly represented in the PALM training.

Eye Tracking Glasses
Simulator

2 versions available

Eye Movements During Dynamic Visual Search

Year: 2021

Authors: M Tong, C Xue, X Lee, X Du, J Wu

Human visual search performance in dynamic environment will be affected by the moving speed of background and object. Eye movement data can help us understand the reasons for this performance difference. This study investigated the changes of eye movement index of visual search under different task difficulty (high, low) and different moving speed (low, high). The results show that the moving speed of the object will affect the fixation numbers, fixation time, saccade amplitude and saccade speed. With the increase of speed, the number of fixation will increase significantly, and the fixation time, saccade amplitude and saccade speed will decrease significantly. Moreover, this index has nothing to do with the difficulty of the search task in this study. The research results can provide guidance for visual search design in dynamic environment.

Eye Tracking Glasses
Software

1 version available:

Functional resonance analysis in an overtaking situation in road traffic: comparing the performance variability mechanisms between human and automation

Year: 2021

Authors: N Grabbe, A Gales, M Höcher,K Bengler

Automated driving promises great possibilities in traffic safety advancement, frequently assuming that human error is the main cause of accidents, and promising a significant decrease in road accidents through automation. However, this assumption is too simplistic and does not consider potential side effects and adaptations in the socio-technical system that traffic represents. Thus, a differentiated analysis, including the understanding of road system mechanisms regarding accident development and accident avoidance, is required to avoid adverse automation surprises, which is currently lacking. This paper, therefore, argues in favour of Resilience Engineering using the functional resonance analysis method (FRAM) to reveal these mechanisms in an overtaking scenario on a rural road to compare the contributions between the human driver and potential automation, in order to derive system design recommendations. Finally, this serves to demonstrate how FRAM can be used for a systemic function allocation for the driving task between humans and automation. Thus, an in-depth FRAM model was developed for both agents based on document knowledge elicitation and observations and interviews in a driving simulator, which was validated by a focus group with peers. Further, the performance variabilities were identified by structured interviews with human drivers as well as automation experts and observations in the driving simulator. Then, the aggregation and propagation of variability were analysed focusing on the interaction and complexity in the system by a semi-quantitative approach combined with a Space-Time/Agency framework. Finally, design recommendations for managing performance variability were proposed in order to enhance system safety. The outcomes show that the current automation strategy should focus on adaptive automation based on a human-automation collaboration, rather than full automation. In conclusion, the FRAM analysis supports decision-makers in enhancing safety enriched by the identification of non-linear and complex risks.

Simulator
Software

11 versions available

Hey, watch where you’re going! An on-road study of driver scanning failures towards pedestrians and cyclists

Year: 2021

Authors: N Kaya, J Girgis, B Hansma,B Donmez

The safety of Vulnerable Road Users (VRUs), such as pedestrians and cyclists, is a serious public health concern, especially at urban intersections. A major reason for vehicle-VRU collisions is driver attentional errors. Prior studies suggest that cross-modal transportation experiences (e.g., being a driver who also cycles) improve visual attention allocation toward VRUs. However, these studies were conducted in simulators or in a laboratory, limiting their generalizability to real world driving. We utilized an instrumented vehicle equipped with eye tracking technology to examine (a) the prevalence of drivers’ visual scanning failures toward VRUs at real intersections and (b) whether there is an effect of cycling experience on this prevalence. Twenty-six experienced drivers (13 cyclists and 13 non-cyclists), between the ages of 35 and 54, completed 18 different turns at urban Toronto intersections, for which gaze and video data were utilized to determine drivers’ visual scanning failures towards areas where conflicting VRUs could approach. Among the 443 unique turn events, 25% were identified as having a visual scanning failure. Results from a mixed effects logit model showed that the odds of committing visual scanning failures towards VRUs during a turning maneuver at an intersection were 2.01 times greater for drivers without cycling experience compared to drivers with cycling experience. Given that our participants represented a low crash-risk age group, this study suggests that the rate at which VRUs are unattended to may be much higher.

Eye Tracking Glasses
Software

6 versions available

How will drivers take back control in automated vehicles? A driving simulator test of an interleaving framework

Year: 2021

Authors: D Nagaraju,A Ansah,NAN Ch,C Mills

We explore the transfer of control from an automated vehicle to the driver. Based on data from N=19 participants who participated in a driving simulator experiment, we find evidence that the transfer of control often does not take place in one step. In other words, when the automated system requests the transfer of control back to the driver, the driver often does not simply stop the non-driving task. Rather, the transfer unfolds as a process of interleaving the non-driving and driving tasks. We also find that the process is moderated by the length of time available for the transfer of control: interleaving is more likely when more time is available. Our interface designs for automated vehicles must take these results into account so as to allow drivers to safely take back control from automation.

Eye Tracking Glasses
Simulator

4 versions available