Driving Performance Research in Foggy Conditions Based on Driving Simulator

2016 ◽  
pp. 477-483 ◽  
Author(s):  
Xiufeng Chen ◽  
Jiabin Tian ◽  
Xianghua Xu
Keyword(s):  
Driving Simulator ◽  
Driving Performance ◽  
Performance Research

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 The impact of postbariatric hypoglycemia on driving performance – a randomized, single‐blind, two‐period crossover study in a driving simulator

2021 ◽  
Author(s):  
Vera Lehmann ◽  
Afroditi Tripyla ◽  
David Herzig ◽  
Jasmin Meier ◽  
Nicolas Banholzer ◽  
...  
Keyword(s):  
Crossover Study ◽  
Driving Simulator ◽  
Driving Performance ◽  
The Impact ◽  
Single Blind

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

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.

scholarly journals Impact of Age-Related Vision Changes on Driving

2020 ◽  
Vol 17 (20) ◽  
pp. 7416
Author(s):  
Sonia Ortiz-Peregrina ◽  
Carolina Ortiz ◽  
Miriam Casares-López ◽  
José J. Castro-Torres ◽  
Luis Jiménez del Barco ◽  
...  
Keyword(s):  
Linear Regression ◽  
Visual Function ◽  
Driving Simulator ◽  
Multiple Linear Regression Model ◽  
Driving Performance ◽  
Older Drivers ◽  
Linear Regression Models ◽  
Simulated Driving ◽  
Age Related ◽  
Intraocular Straylight

Aging leads to impaired visual function, which can affect driving—a very visually demanding task—and has a direct impact on an individual’s quality of life if their license is withdrawn. This study examined the associations between age-related vision changes and simulated driving performance. To this end, we attempted to determine the most significant visual parameters in terms of evaluating elderly drivers’ eyesight. Twenty-one younger drivers (aged 25–40) were compared to 21 older drivers (aged 56–71). Study participants were assessed for visual acuity, contrast sensitivity, halos, and intraocular straylight, which causes veiling luminance on the retina and degrades vision. Driving performance was evaluated using a driving simulator. The relationships between simulated driving performance and the visual parameters tested were examined with correlation analyses and linear regression models. Older drivers presented impairment in most visual parameters (p < 0.05), with straylight being the most significantly affected (we also measured the associated effect size). Older drivers performed significantly worse (p < 0.05) in the simulator test, with a markedly lower performance in lane stability. The results of the multiple linear regression model evidenced that intraocular straylight is the best visual parameter for predicting simulated driving performance (R2 = 0.513). Older drivers have shown significantly poorer results in several aspects of visual function, as well as difficulties in driving simulator performance. Our results suggest that the non-standardized straylight evaluation could be significant in driver assessments, especially at the onset of age-related vision changes.

scholarly journals Timelined multimodal recording of EEG and driving performance using a driving simulator system during a focal impaired awareness seizure

2020 ◽  
Vol 13 ◽  
pp. 100356 ◽  
Author(s):  
Tomoaki Ban ◽  
Yohei Ishishita ◽  
Masayuki Tetsuka ◽  
Taku Uchiyama ◽  
Keisuke Ohtani ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Driving Performance ◽  
Impaired Awareness

scholarly journals Testing the Effectiveness of a Mixed-Method Pilot Intervention in Reducing Risky Driving Due to Aggression and Stress

Safety ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Maria Papadakaki ◽  
Nikolaos Stamou ◽  
Stefanos Bessas ◽  
Stavroula Lioliou ◽  
Jooannes Chliaoutakis
Keyword(s):  
Mixed Method ◽  
Large Scale ◽  
Driving Simulator ◽  
Intervention Group ◽  
Cognitive Restructuring ◽  
Driving Performance ◽  
Control Group ◽  
Driving Behaviors ◽  
Experiential Instruction ◽  
Pilot Intervention

The study aimed at testing the effectiveness of a mixed-method pilot intervention in reducing risky self-reported driving performance, upon addressing stress and aggression while driving. The study recruited individuals who had performed these behaviors during the year preceding the study and allocated them into an intervention (n = 10) and a control group (n = 30). A pre-and postintervention evaluation design was employed to explore changes in risky self-reported driving behaviors, 12 months after the intervention. The intervention involved 2 h of experiential instruction and 1 h of cognitive restructuring using a driving simulator and scenarios appropriate for the processing of driving stress, aggression, and risk. The intervention group displayed significant improvements in the scales of “Hazard Monitoring” (p = 0.037) and “Covered Violations” (p = 0.049) at the postintervention level. No statistically significant differences were identified in terms of self-reported driving performance between the intervention and the control group at postintervention level. Launching large-scale experimental surveys with broadened cognitive restructuring approaches seems important to deepen our understanding of the behavioral change processes and increase the effectiveness of future interventions.

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