Smartwatches vs. Smartphones

2019 ◽  
pp. 453-473
Author(s):  
Wayne C.W. Giang ◽  
Huei-Yen Winnie Chen ◽  
Birsen Donmez
Keyword(s):  
Perceived Risk ◽  
Driving Simulator ◽  
Reaction Times ◽  
Driving Performance ◽  
Read Aloud ◽  
Smart Devices ◽  
Actual Performance ◽  
Common View ◽  
Smartphone Use ◽  
Lane Position

This work seeks to understand whether the unique features of a smartwatch, compared to a smartphone, mitigate or exacerbate driver distraction due to notifications, and to provide insights about drivers' perceptions of the risks associated with using smartwatches while driving. As smartwatches are gaining popularity among consumers, there is a need to understand how smartwatch use may influence driving performance. Previous driving research has examined voice calling on smartwatches, but not interactions with notifications, a key marketed feature. Engaging with notifications (e.g., reading and texting) on a handheld device is a known distraction associated with increased crash risks. Two driving simulator studies compared smartwatch to smartphone notifications. Experiment I asked participants to read aloud brief text notifications and Experiment II had participants manually select a response to arithmetic questions presented as notifications. Both experiments investigated the resulting glances to and physical interactions with the devices, as well as self-reported risk perception. Experiment II also investigated driving performance and self-reported knowledge/expectation about legislation surrounding the use of smart devices while driving. Experiment I found that participants were faster to visually engage with the notification on the smartwatch than the smartphone, took longer to finish reading aloud the notifications, and exhibited more glances longer than 1.6 s. Experiment II found that participants took longer to reply to notifications and had longer overall glance durations on the smartwatch than the smartphone, along with longer brake reaction times to lead vehicle braking events. Compared to the no device baseline, both devices increased lane position variability and resulted in higher self-reported perceived risk. Experiment II participants also considered that smartwatch use while driving deserves penalties equal to or less than smartphone use. The findings suggest that smartwatches may have road safety consequences. Given the common view among participants to associate smartwatch use with equal or less traffic penalties than smartphone use, there may be a disconnect between drivers' actual performance and their perceptions about smartwatch use while driving.

Smartwatches vs. Smartphones

2017 ◽  
Vol 9 (2) ◽  
pp. 39-57 ◽  
Author(s):  
Wayne C.W. Giang ◽  
Huei-Yen Winnie Chen ◽  
Birsen Donmez
Keyword(s):  
Perceived Risk ◽  
Driving Simulator ◽  
Reaction Times ◽  
Driving Performance ◽  
Smart Devices ◽  
Actual Performance ◽  
Common View ◽  
Handheld Device ◽  
Smartphone Use ◽  
Lane Position

This work seeks to understand whether the unique features of a smartwatch, compared to a smartphone, mitigate or exacerbate driver distraction due to notifications, and to provide insights about drivers' perceptions of the risks associated with using smartwatches while driving. As smartwatches are gaining popularity among consumers, there is a need to understand how smartwatch use may influence driving performance. Previous driving research has examined voice calling on smartwatches, but not interactions with notifications, a key marketed feature. Engaging with notifications (e.g., reading and texting) on a handheld device is a known distraction associated with increased crash risks. Two driving simulator studies compared smartwatch to smartphone notifications. Experiment I asked participants to read aloud brief text notifications and Experiment II had participants manually select a response to arithmetic questions presented as notifications. Both experiments investigated the resulting glances to and physical interactions with the devices, as well as self-reported risk perception. Experiment II also investigated driving performance and self-reported knowledge/expectation about legislation surrounding the use of smart devices while driving. Experiment I found that participants were faster to visually engage with the notification on the smartwatch than the smartphone, took longer to finish reading aloud the notifications, and exhibited more glances longer than 1.6 s. Experiment II found that participants took longer to reply to notifications and had longer overall glance durations on the smartwatch than the smartphone, along with longer brake reaction times to lead vehicle braking events. Compared to the no device baseline, both devices increased lane position variability and resulted in higher self-reported perceived risk. Experiment II participants also considered that smartwatch use while driving deserves penalties equal to or less than smartphone use. The findings suggest that smartwatches may have road safety consequences. Given the common view among participants to associate smartwatch use with equal or less traffic penalties than smartphone use, there may be a disconnect between drivers' actual performance and their perceptions about smartwatch use while driving.

Driving Performance of Residents after Six Consecutive Overnight Work Shifts

2016 ◽  
Vol 124 (6) ◽  
pp. 1396-1403 ◽  
Author(s):  
Julie L. Huffmyer ◽  
Matthew Moncrief ◽  
Jessica A. Tashjian ◽  
Amanda M. Kleiman ◽  
David C. Scalzo ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Motor Vehicle ◽  
Reaction Times ◽  
Driving Performance ◽  
Guidance System ◽  
Driving Safety ◽  
Experimental Session ◽  
Consecutive Night ◽  
Resident Physicians ◽  
Night Shifts

Abstract Background Residency training requires work in clinical settings for extended periods of time, resulting in altered sleep patterns, sleep deprivation, and potentially deleterious effects on safe performance of daily activities, including driving a motor vehicle. Methods Twenty-nine anesthesiology resident physicians in postgraduate year 2 to 4 drove for 55 min in the Virginia Driving Safety Laboratory using the Driver Guidance System (MBFARR, LLC, USA). Two driving simulator sessions were conducted, one experimental session immediately after the final shift of six consecutive night shifts and one control session at the beginning of a normal day shift (not after call). Both sessions were conducted at 8:00 am. Psychomotor vigilance task testing was employed to evaluate reaction time and lapses in attention. Results After six consecutive night shifts, residents experienced significantly impaired control of all the driving variables including speed, lane position, throttle, and steering. They were also more likely to be involved in collisions. After six consecutive night shifts, residents had a significant increase in reaction times (281.1 vs. 298.5 ms; P = 0.001) and had a significant increase in the number of both minor (0.85 vs. 1.88; P = 0.01) and major lapses (0.00 vs. 0.31; P = 0.008) in attention. Conclusions Resident physicians have greater difficulty controlling speed and driving performance in the driving simulator after six consecutive night shifts. Reaction times are also increased with emphasis on increases in minor and major lapses in attention after six consecutive night shifts.

scholarly journals Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving

2021 ◽  
Vol 5 (4) ◽  
pp. 21
Author(s):  
Clemens Schartmüller ◽  
Klemens Weigl ◽  
Andreas Löcken ◽  
Philipp Wintersberger ◽  
Marco Steinhauser ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Reaction Times ◽  
Driving Performance ◽  
Automated Driving ◽  
Auditory Condition ◽  
Safety Critical ◽  
The Road ◽  
Within Subjects ◽  
On The Road ◽  
Vehicle Automation

(1) Background: Primary driving tasks are increasingly being handled by vehicle automation so that support for non-driving related tasks (NDRTs) is becoming more and more important. In SAE L3 automation, vehicles can require the driver-passenger to take over driving controls, though. Interfaces for NDRTs must therefore guarantee safe operation and should also support productive work. (2) Method: We conducted a within-subjects driving simulator study (N=53) comparing Heads-Up Displays (HUDs) and Auditory Speech Displays (ASDs) for productive NDRT engagement. In this article, we assess the NDRT displays’ effectiveness by evaluating eye-tracking measures and setting them into relation to workload measures, self-ratings, and NDRT/take-over performance. (3) Results: Our data highlights substantially higher gaze dispersion but more extensive glances on the road center in the auditory condition than the HUD condition during automated driving. We further observed potentially safety-critical glance deviations from the road during take-overs after a HUD was used. These differences are reflected in self-ratings, workload indicators and take-over reaction times, but not in driving performance. (4) Conclusion: NDRT interfaces can influence visual attention even beyond their usage during automated driving. In particular, the HUD has resulted in safety-critical glances during manual driving after take-overs. We found this impacted workload and productivity but not driving performance.

Effects of Individual Differences, Attention, and Memory Deficits on Driver Distraction

2020 ◽  
Vol 64 (1) ◽  
pp. 1196-1201
Author(s):  
Alejandro A. Arca ◽  
Kaitlin M. Stanford ◽  
Mustapha Mouloua
Keyword(s):  
Individual Differences ◽  
Driving Simulator ◽  
Memory Deficits ◽  
Driving Performance ◽  
Driver Distraction ◽  
Phone Call ◽  
Traffic Density ◽  
Attention And Memory ◽  
Adhd Diagnosis ◽  
Simulated Driving

The current study was designed to empirically examine the effects of individual differences in attention and memory deficits on driver distraction. Forty-eight participants consisting of 37 non-ADHD and 11 ADHD drivers were tested in a medium fidelity GE-ISIM driving simulator. All participants took part in a series of simulated driving scenarios involving both high and low traffic conditions in conjunction with completing a 20-Questions task either by text- message or phone-call. Measures of UFOV, simulated driving, heart rate variability, and subjective (NASA TLX) workload performance were recorded for each of the experimental tasks. It was hypothesized that ADHD diagnosis, type of cellular distraction, and traffic density would affect driving performance as measured by driving performance, workload assessment, and physiological measures. Preliminary results indicated that ADHD diagnosis, type of cellular distraction, and traffic density affected the performance of the secondary task. These results provide further evidence for the deleterious effects of cellphone use on driver distraction, especially for drivers who are diagnosed with attention-deficit and memory capacity deficits. Theoretical and practical implications are discussed, and directions for future research are also presented.

scholarly journals Driving Performance and Its Correlation with Neuropsychological Tests in Senior Drivers with Cognitive Impairment in Japan

2021 ◽  
Vol 79 (4) ◽  
pp. 1575-1587
Author(s):  
Zhouyuan Peng ◽  
Hiroyuki Nishimoto ◽  
Ayae Kinoshita
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Functions ◽  
Neuropsychological Tests ◽  
Driving Simulator ◽  
Driving Performance ◽  
Impaired Driving ◽  
Dementia Patients ◽  
Neuropsychological Factors ◽  
Senior Drivers

Background: With the rapid aging of the population, the issue of driving by dementia patients has been causing increasing concern worldwide. Objective: To investigate the driving difficulties faced by senior drivers with cognitive impairment and identify the specific neuropsychological tests that can reflect specific domains of driving maneuvers. Methods: Senior drivers with cognitive impairment were investigated. Neuropsychological tests and a questionnaire on demographic and driving characteristics were administered. Driving simulator tests were used to quantify participants’ driving errors in various domains of driving. Results: Of the 47 participants, 23 current drivers, though they had better cognitive functions than 24 retired drivers, were found to have impaired driving performance in the domains of Reaction, Starting and stopping, Signaling, and Overall (wayfinding and accidents). The parameters of Reaction were significantly related to the diagnosis, and the scores of MMSE, TMT-A, and TMT-B. As regards details of the driving errors, “Sudden braking” was associated with the scores of MMSE (ρ= –0.707, p < 0.01), BDT (ρ= –0.560, p < 0.05), and ADAS (ρ= 0.758, p < 0.01), “Forgetting to use turn signals” with the TMT-B score (ρ= 0.608, p < 0.05), “Centerline crossings” with the scores of MMSE (ρ= –0.582, p < 0.05) and ADAS (ρ= 0.538, p < 0.05), and “Going the wrong way” was correlated with the score of CDT (ρ= –0.624, p < 0.01). Conclusion: Different neuropsychological factors serve as predictors of different specific driving maneuvers segmented from driving performance.

Driving Performance Deficits Despite Concussion Symptom Resolution: A Case Report

2018 ◽  
Vol 23 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Nicole L. Hoffman ◽  
Hannes Devos ◽  
Julianne D. Schmidt
Keyword(s):  
Case Report ◽  
Cognitive Deficits ◽  
Processing Speed ◽  
Driving Simulator ◽  
Driving Performance ◽  
Performance Study ◽  
Male College Student ◽  
Performance Deficits ◽  
Male College ◽  
Complex Attention

Driving performance prior to concussion is not commonly available to help clinicians identify when deficits return to a preinjury status. This case report examines driving performance prior to and following concussion in a 20-year-old male college student. He initially volunteered as a control for a separate driving performance study. He sustained a concussion 18 months later, and was asked to complete the same driving tasks as previous testing once he was asymptomatic. Poor driving simulator performance and subtle cognitive deficits in complex attention and processing speed were evident despite being symptom-free. Our findings may be useful when considering readiness to drive postconcussion.

scholarly journals Fragrance Impact on Driving Performance

2016 ◽  
Vol 2 (5) ◽  
pp. 21
Author(s):  
Masria Mustafa ◽  
Norazni Rustam ◽  
Rosfaiizah Siran
Keyword(s):  
Open Access ◽  
Peer Review ◽  
Driving Simulator ◽  
Human Subjects ◽  
Publishing House ◽  
Driving Performance ◽  
Speed Reduction ◽  
International Publishing ◽  
Open Access Article

Previous studies have indicated that certain types of fragrance in the vehicle are useful in keeping the driver alert. This study was conducted to evaluate the effect of lavender or vanilla flavor fragrances toward driving performance. Ten human subjects were tested using the driving simulator in three different conditions; driving with vanilla, lavender flavor fragrance and driving without fragrance. A questionnaire was distributed to examine the emotion states of the driver after driving the simulator. Our results indicate that fragrance did not affect the speed reduction. The emotions of the drivers were calm due to the presence of the fragrance.2398-4279 © 2017 The Authors. Published for AMER ABRA by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, UniversitiTeknologi MARA, Malaysia.Keywords: driving performance, vehicle fragrance, speed reduction

The Effects of Cognitive and Visual Workload on Peripheral Detection in the Detection Response Task

2018 ◽  
Vol 60 (6) ◽  
pp. 855-869 ◽  
Author(s):  
Wim van Winsum
Keyword(s):  
Cognitive Load ◽  
Driving Simulator ◽  
Response Times ◽  
Cognitive Task ◽  
Theory Development ◽  
Reaction Times ◽  
Task Load ◽  
Detection Response ◽  
Response Task ◽  
Stimulus Eccentricity

Objective: The independent effects of cognitive and visual load on visual Detection Response Task (vDRT) reaction times were studied in a driving simulator by performing a backwards counting task and a simple driving task that required continuous focused visual attention to the forward view of the road. The study aimed to unravel the attentional processes underlying the Detection Response Task effects. Background: The claim of previous studies that performance degradation on the vDRT is due to a general interference instead of visual tunneling was challenged in this experiment. Method: vDRT stimulus eccentricity and stimulus conspicuity were applied as within-subject factors. Results: Increased cognitive load and visual load both resulted in increased response times (RTs) on the vDRT. Cognitive load increased RT but revealed no task by stimulus eccentricity interaction. However, effects of visual load on RT showed a strong task by stimulus eccentricity interaction under conditions of low stimulus conspicuity. Also, more experienced drivers performed better on the vDRT while driving. Conclusion: This was seen as evidence for a differential effect of cognitive and visual workload. The results supported the tunnel vision model for visual workload, where the sensitivity of the peripheral visual field reduced as a function of visual load. However, the results supported the general interference model for cognitive workload. Application: This has implications for the diagnosticity of the vDRT: The pattern of results differentiated between visual task load and cognitive task load. It also has implications for theory development and workload measurement for different types of tasks.

Enhancing the Performance of a Model to Predict Driving Distraction with the Random Forest Classifier

2021 ◽  
pp. 036119812110186
Author(s):  
Samira Ahangari ◽  
Mansoureh Jeihani ◽  
Anam Ardeshiri ◽  
Md Mahmudur Rahman ◽  
Abdollah Dehzangi
Keyword(s):  
Random Forest ◽  
Driving Simulator ◽  
Situational Awareness ◽  
True Positive Rate ◽  
The United States ◽  
Driving Performance ◽  
Lane Changing ◽  
Wide Range ◽  
Positive Rate ◽  
Better Than

Distracted driving is known to be one of the main causes of crashes in the United States, accounting for about 40% of all crashes. Drivers’ situational awareness, decision-making, and driving performance are impaired as a result of temporarily diverting their attention from the primary task of driving to other unrelated tasks. Detecting driver distraction would help in adapting the most effective countermeasures. To tackle this problem, we employed a random forest (RF) classifier, one of the best classifiers that has attained promising results for a wide range of problems. Here, we trained RF using the data collected from a driving simulator, in which 92 participants drove under six different distraction scenarios of handheld calling, hands-free calling, texting, voice command, clothing, and eating/drinking on four different road classes (rural collector, freeway, urban arterial, and local road in a school zone). Various driving performance measures such as speed, acceleration, throttle, lane changing, brake, collision, and offset from the lane center were investigated. Using the RF method, we achieved 76.5% prediction accuracy on the independent test set, which is over 8.2% better than results reported in previous studies. We also obtained a 76.6% true positive rate, which is 14% better than those reported in previous studies. Such results demonstrate the preference of RF over other machine learning methods to identify driving distractions.

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