Driver Distraction: Evaluation with Event Detection Paradigm

2003 ◽  
Vol 1843 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Jeff Greenberg ◽  
Louis Tijerina ◽  
Reates Curry ◽  
Bruce Artz ◽  
Larry Cathey ◽  
...  
Keyword(s):  
Performance Measures ◽  
Event Detection ◽  
Driving Simulator ◽  
Vehicle Control ◽  
Driving Performance ◽  
Driver Distraction ◽  
Adult Group ◽  
Climate Control ◽  
Moving Base ◽  
Teenage Drivers

The effects of eight in-vehicle tasks on driver distraction were measured in a large, moving-base driving simulator. Forty-eight adults, ranging in age from 35 to 66, and 15 teenagers participated in the simulated drive. Hand-held and hands-free versions of phone dialing, voicemail retrieval, and incoming calls represented six of the eight tasks. Manual radio tuning and climate control adjustment were also included to allow comparison with tasks that have traditionally been present in vehicles. During the drive the participants were asked to respond to sudden movements in surrounding traffic. The driver’s ability to detect these sudden movements or events changed with the nature of the in-vehicle tasks that were being performed. Driving performance measures such as lane violations and heading error were also computed. The performance of the adult group was compared with the performance of the teenage drivers. Compared with the adults, the teens were found to choose unsafe following distances, have poor vehicle control skills, and be more prone to distraction from hand-held phone tasks.

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.

Comparison of Primary and Secondary Task Measures as a Function of Simulated Vehicle Dynamics and Driving Conditions

1978 ◽  
Vol 20 (2) ◽  
pp. 233-244 ◽  
Author(s):  
Walter W. Wierwille ◽  
James C. Gutmann
Keyword(s):  
Task Performance ◽  
Vehicle Dynamics ◽  
Secondary Task ◽  
Driving Simulator ◽  
Driving Performance ◽  
Independent Variables ◽  
Moving Base ◽  
High Workload ◽  
Driving Task ◽  
Task Measure

In a previously reported experiment involving a moving base driving simulator with computer-generated display, secondary task measures of workload showed significant increases as a function of large changes in vehicle dynamics and disturbance levels. Because the secondary task measures appeared less sensitive than desired, driving performance measures recorded during the same experiment were later analyzed. Particular emphasis in examining the driving performance data was placed on (1) determining the degree of intrusion of the secondary task on the driving task as a function of the independent variables, and (2) on comparing the sensitivity of the primary and secondary task measures. The results showed the secondary task does intrude significantly upon the driving task performance at low workload levels, but that it does not significantly intrude at high workload levels. Also, when the four primary task measures were analyzed for sensitivity to the independent variables, new information was obtained indicating greater sensitivity than is obtained with the single secondary task measure. Steering ratio, for example, is found to affect performance at high disturbance levels—a result not obtained in examining the secondary task by itself. The merits of primary and secondary task performance analysis are discussed, and suggestions are made for future work.

Driver Drowsiness Detection Using Subsidiary Task and Driving Performance Measures

1986 ◽  
Vol 30 (4) ◽  
pp. 398-402 ◽  
Author(s):  
H. Lenora Hardee ◽  
Thomas A. Dingus ◽  
Walter W. Wierwille
Keyword(s):  
Performance Measures ◽  
Driving Performance ◽  
Physiological Measures ◽  
Stimulus Input ◽  
Linear Discriminant ◽  
Input Modality ◽  
Driver Drowsiness ◽  
Moving Base ◽  
Response Measures ◽  
Discriminant Analyses

Six male and six female subjects operated a moving-base automobile simulator for 2 1/2 hours after having been kept continuously awake for approximately 19 hours past their normal wake-up times. During this session, subjects drove both while performing three subsidiary tasks (auditory, visual, and tactual) which required a tactual output but which otherwise differed only in terms of stimulus input modality, and while performing no task. The driving performance, behavioral, physiological, and subsidiary task response measures collected during the experiment were subjected to a series of linear discriminant analyses, and the results indicated that the detection of driver impairment due to drowsiness may indeed be possible by monitoring combinations of subsidiary task and physiological measures.

scholarly journals Glaucomatous visual fields and neurocognitive function are independently associated with poor lane maintenance during driving simulation

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
David E. Anderson ◽  
John P. Bader ◽  
Emily A. Boes ◽  
Meghal Gagrani ◽  
Lynette M. Smith ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Vehicle Control ◽  
Driving Behavior ◽  
Driving Performance ◽  
Driving Simulation ◽  
Sensor Data ◽  
Lateral Acceleration ◽  
Steering Wheel ◽  
Neurocognitive Performance ◽  
Loss Severity

Abstract Background Driving simulators are a safe alternative to on-road vehicles for studying driving behavior in glaucoma drivers. Visual field (VF) loss severity is associated with higher driving simulator crash risk, though mechanisms explaining this relationship remain unknown. Furthermore, associations between driving behavior and neurocognitive performance in glaucoma are unexplored. Here, we evaluated the hypothesis that VF loss severity and neurocognitive performance interact to influence simulated vehicle control in glaucoma drivers. Methods Glaucoma patients (n = 25) and suspects (n = 18) were recruited into the study. All had > 20/40 corrected visual acuity in each eye and were experienced field takers with at least three stable (reliability > 20%) fields over the last 2 years. Diagnosis of neurological disorder or cognitive impairment were exclusion criteria. Binocular VFs were derived from monocular Humphrey VFs to estimate a binocular VF index (OU-VFI). Montreal Cognitive Assessment (MoCA) was administered to assess global and sub-domain neurocognitive performance. National Eye Institute Visual Function Questionnaire (NEI-VFQ) was administered to assess peripheral vision and driving difficulties sub-scores. Driving performance was evaluated using a driving simulator with a 290° panoramic field of view constructed around a full-sized automotive cab. Vehicle control metrics, such as lateral acceleration variability and steering wheel variability, were calculated from vehicle sensor data while patients drove on a straight two-lane rural road. Linear mixed models were constructed to evaluate associations between driving performance and clinical characteristics. Results Patients were 9.5 years older than suspects (p = 0.015). OU-VFI in the glaucoma group ranged from 24 to 98% (85.6 ± 18.3; M ± SD). OU-VFI (p = .0066) was associated with MoCA total (p = .0066) and visuo-spatial and executive function sub-domain scores (p = .012). During driving simulation, patients showed greater steering wheel variability (p = 0.0001) and lateral acceleration variability (p < .0001) relative to suspects. Greater steering wheel variability was independently associated with OU-VFI (p = .0069), MoCA total scores (p = 0.028), and VFQ driving sub-scores (p = 0.0087), but not age (p = 0.61). Conclusions Poor vehicle control was independently associated with greater VF loss and worse neurocognitive performance, suggesting both factors contribute to information processing models of driving performance in glaucoma. Future research must demonstrate the external validity of current findings to on-road performance in glaucoma.

Proposal for Driver Distraction Indexes Using Biological Signals

2012 ◽  
Author(s):  
Michiko Ohkura ◽  
Kazuma Uchiumi ◽  
Yukou Saito ◽  
Koyo Hasegawa
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Driving Performance ◽  
Driver Distraction ◽  
Experimental Results ◽  
Major Contributor ◽  
Vehicle Crashes ◽  
Biological Signals ◽  
Driver Inattention ◽  
Driving Task

According to the AAA Foundation for Traffic Safety, driver inattention is a major contributor to highway accidents. Driver distraction is one form of inattention and a leading factor in most vehicle crashes and near crashes. Distraction occurs when a driver is delayed in the recognition of information needed to safely accomplish the driving task because some event, activity, object, or person within or outside the vehicle compels or induces the driver attention away from the driving task. Although some indexes of driving performance have measured distraction, they are the results of the distraction and not the distraction itself. We directly and quantitatively employ biological signals to measure the distraction by finding useful biological indexes from candidates of various biological signals. Our experimental results using a driving simulator showed useful indexes derived from EEG and ECG.

Positive Bias in Teenage Drivers With ADHD Within a Simulated Driving Task

2015 ◽  
Vol 22 (12) ◽  
pp. 1150-1157 ◽  
Author(s):  
Gregory A. Fabiano ◽  
Nicole K. Schatz ◽  
Kevin F. Hulme ◽  
Karen L. Morris ◽  
Rebecca K. Vujnovic ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Behavior Disorder ◽  
Driving Performance ◽  
Driving Ability ◽  
Disruptive Behavior Disorder ◽  
Global Rating ◽  
Positive Bias ◽  
Driving Behaviors ◽  
Teenage Drivers ◽  
Youth With Adhd

Objective: Youth with ADHD exhibit positive bias, an overestimation of ability, relative to external indicators. The positive bias construct is understudied in adolescents, particularly in the domain of driving. Study is needed as youth with ADHD experience greater negative outcomes in driving relative to typically developing teens. Method: Positive bias on a driving simulator task was investigated with 172 teenagers with ADHD, combined type. Youth participated in a driving simulation task and rated driving performance afterward. Results: Compared with external ratings of driving performance, youth overestimated driving competence for specific driving behaviors as well as globally. The global rating demonstrated a greater degree of positive bias. Greater positive bias on global ratings of driving ability also predicted greater rates of risky driving behaviors during the simulator exercise independent from disruptive behavior disorder symptoms. Conclusion: Results inform prevention and intervention efforts for teenage drivers with ADHD.

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop

2020 ◽  
pp. 001872082094328
Author(s):  
Lisa Graichen ◽  
Matthias Graichen ◽  
Josef F. Krems
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Driving Simulator ◽  
Negative Impact ◽  
Driving Behavior ◽  
Driving Performance ◽  
Driver Distraction ◽  
Safe Alternative ◽  
Visual Distraction ◽  
Performance Effects

Objective We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs). Background As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception. Thus, the implementation of new interaction systems that use midair gestures to encourage glance-free interactions could reduce visual distraction among drivers. Methods In this experiment, participants drove a projection-based Vehicle-in-the-Loop. The projection-based technology combines a visual simulation with kinesthetic, vestibular, and auditory feedback from a car on a test track. While driving, participants used GBI or TBI to perform IVIS tasks. To investigate driving behavior related to critical driving situations and car-following maneuvers, vehicle data based upon longitudinal and lateral driving were collected. Results Participants reacted faster to critical driving situations when using GBI compared to TBI. For drivers using TBI, steering performance decreased and time headway to a preceding vehicle was higher. Conclusion Gestures provide a safe alternative to in-vehicle interactions. Moreover, GBI has fewer effects on driver distraction than TBI. Application Potential applications of this research include all in-vehicle interaction systems used by drivers.

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