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Total results: 588

Driver Scanning Behavior at Urban and Suburban Intersections: An On-Road Approach

Year: 2021

Authors: J Girgis

Urban and suburban intersections present unique challenges for drivers, requiring them to divide their attention between multiple sources of information. This dissertation investigates driver scanning behavior at these intersections using an on-road approach to gather real-world data. The findings suggest significant differences in how drivers scan their environment in urban versus suburban settings, which has implications for the design of intersection safety interventions. By understanding these behaviors, transportation authorities can develop more effective strategies to reduce accidents and enhance road safety. This research provides valuable insights into driver behavior that can inform future transportation planning and policy-making.

3 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%.

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.

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.

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.

7 versions available

Examining the effect of online advertisement cues on human responses using eye-tracking, EEG, and MRI

Year: 2021

Authors: C Yen, MC Chiang

This study sought to emphasize how disciplines such as neuroscience and marketing can be applied in advertising and consumer behavior. The application of neuroscience methods in analyzing and understanding human behavior related to the Elaboration Likelihood Model (ELM) and brain activity has recently garnered attention. This study examines brain processes while participants attempted to elicit preferences for a product, and demonstrates factors that influence consumer behavior using eye-tracking, electroencephalography (EEG), and magnetic resonance imaging (MRI) from a neuroscience approach. We planned two conditions of online advertising, namely, peripheral cues without argument and central cues with argument strength. Thirty respondents participated in the experiment, consisting of eye-tracking, EEG, and MRI instruments to explore brain activity in central cue conditions. We investigated whether diffusion tensor imaging (DTI) analysis could detect regional brain changes. Using eye-tracking, we found that the responses were mainly in the mean fixation duration, number of fixations, mean saccade duration, and number of saccade durations for the central cue condition. Moreover, the findings show that the fusiform gyrus and frontal cortex are significantly associated with building a relationship by inferring central cues in the EEG assay. The MRI images show that the fusiform gyrus and frontal cortex are significantly active in the central cue condition. DTI analysis indicates that the corpus callosum has changed in the central cue condition. We used eye-tracking, EEG, MRI, and DTI to understand that these connections may apprehend responses when viewing advertisements, especially in the fusiform gyrus, frontal cortex, and corpus callosum.

4 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.

3 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.

1 version available:

Eye tracking algorithms, techniques, tools, and applications with an emphasis on machine learning and Internet of Things technologies

Year: 2021

Authors: AF Klaib,NO Alsrehin, WY Melhem

Eye tracking is the process of measuring where one is looking (point of gaze) or the motion of an eye relative to the head. Researchers have developed different algorithms and techniques to automatically track the gaze position and direction, which are helpful in different applications. Research on eye tracking is increasing owing to its ability to facilitate many different tasks, particularly for the elderly or users with special needs. This study aims to explore and review eye tracking concepts, methods, and techniques by further elaborating on efficient and effective modern approaches such as machine learning (ML), Internet of Things (IoT), and cloud computing. These approaches have been in use for more than two decades and are heavily used in the development of recent eye tracking applications. The results of this study indicate that ML and IoT are important aspects in evolving eye tracking applications owing to their ability to learn from existing data, make better decisions, be flexible, and eliminate the need to manually re-calibrate the tracker during the eye tracking process. In addition, they show that eye tracking techniques have more accurate detection results compared with traditional event-detection methods. In addition, various motives and factors in the use of a specific eye tracking technique or application are explored and recommended. Finally, some future directions related to the use of eye tracking in several developed applications are described.

1 version available:

Eye–head–trunk coordination while walking and turning in a simulated grocery shopping task

Year: 2021

Authors: K Kim, M Fricke, O Bock

Previous studies argued that body turns are executed in an ordered sequence: the eyes turn first, followed by the head and then by the trunk. The purpose of this study was to find out whether this sequence holds even if body turns are not explicitly instructed, but nevertheless are necessary to reach an instructed distal goal. We asked participants to shop for grocery products in a simulated supermarket. To retrieve each product, they had to walk down an aisle, and then turn left or right into a corridor that led towards the target shelf. The need to make a turn was never mentioned by the experimenter, but it nevertheless was required in order to approach the target shelf. Main variables of interest were the delay between eye and head turns towards the target shelf, as well as the delay between head and trunk turns towards the target shelf. We found that both delays were consistently positive, and that their magnitude was near the top of the range reported in literature. We conclude that the ordered sequence of eye – then head – then trunk turns can be observed not only with a proximal, but also with a distal goal.

8 versions available