Cognitive Distraction While Driving: A Critical Review of Definitions and Prevalence in Crashes

Young, Richard A.

doi:10.4271/2012-01-0967

Cited by 30 publications

(21 citation statements)

References 54 publications

(56 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, as the reporting was not done in real time, it is not clear whether unreported objects had not been detected or just not been processed enough to be stored in memory. Not processing irrelevant objects can even be a meaningful strategy to increase safety under increased mental workload, instead of an indication for reduced performance (Young, Salmon, & Cornelissen, 2013;Young, 2012). No literature on detailed visual behaviour of cyclists performing secondary tasks could be found.…”

Section: Introductionmentioning

confidence: 96%

Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic

Ahlström

Kircher

Thorslund

et al. 2016

Transportation Research Part F: Traffic Psychology and Behaviou

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 96%

Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic

Ahlström

Kircher

Thorslund

et al. 2016

Transportation Research Part F: Traffic Psychology and Behaviou

View full text Add to dashboard Cite

“…Due to obvious road safety implications, the tasks are often naturalistic ones, such as mobile phone handling or usage of in-vehicle navigation systems [2]. But like capability, distraction consists of multiple kinds of phenomena, often divided to visual distraction (“eyes-off-the-road”), cognitive distraction (“mind-off-the-road”) and manual distraction (“hands-off-the-wheel”) [13]. Naturalistic tasks tend to blend some or all of these, which makes them rather difficult to identify and isolate for rigorous analysis.…”

Section: Introductionmentioning

confidence: 99%

Task-Difficulty Homeostasis in Car Following Models: Experimental Validation Using Self-Paced Visual Occlusion

et al. 2017

View full text Add to dashboard Cite

Car following (CF) models used in traffic engineering are often criticized for not incorporating “human factors” well known to affect driving. Some recent work has addressed this by augmenting the CF models with the Task-Capability Interface (TCI) model, by dynamically changing driving parameters as function of driver capability. We examined assumptions of these models experimentally using a self-paced visual occlusion paradigm in a simulated car following task. The results show strong, approximately one-to-one, correspondence between occlusion duration and increase in time headway. The correspondence was found between subjects and within subjects, on aggregate and individual sample level. The long time scale aggregate results support TCI-CF models that assume a linear increase in time headway in response to increased distraction. The short time scale individual sample level results suggest that drivers also adapt their visual sampling in response to transient changes in time headway, a mechanism which isn’t incorporated in the current models.

show abstract

“…3,4 Cognitive load likely increases crash risk by its effects on attentional networks in the brain that increase event response times (RTs), miss rates, and the duration of single glances off the road. 3,4,5 The "Peripheral Detection Task" (PDT) has been proposed as one measure of the attentional effects of cognitive load. 1,3,6,7,8 The PDT measures RTs to, and misses of, peripheral light stimuli during secondary task performance.…”

Section: Introductionmentioning

confidence: 99%

The Tactile Detection Response Task: Preliminary Validation for Measuring the Attentional Effects of Cognitive Load

Young

Hsieh

Seaman

2013

Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

View full text Add to dashboard Cite

Summary: Improved measures of the attentional effects of cognitive load are needed to reduce potential crashes caused by secondary tasks performed while driving. The Tactile Detection Response Task (TDRT) in the proposed ISO Draft Standard WD17488 was tested in laboratory and on-road venues with 16 and 15 subjects, respectively. A sensitivity test used a purely cognitive load increase from an easy (0-back) to hard (1-back) auditory-vocal task. The TDRT response time increased by 90±21 msec in the laboratory, and by 135±34 msec on the road, while the miss rate increased by 4% in the laboratory and 5% on the road, thus validating TDRT sensitivity to an increase in purely cognitive load. A specificity test used a visual load increase with little cognitive load difference from an easy to hard visual-manual "Surrogate Reference Task" (SuRT), to which the TDRT should not respond. The TDRT response time and miss rate to the SuRT did not increase in the laboratory or road as a result of the increased visual load, providing preliminary validation that the TDRT may be both specific and sensitive to the attentional effects of cognitive load.

show abstract

Cognitive Distraction While Driving: A Critical Review of Definitions and Prevalence in Crashes

Cited by 30 publications

References 54 publications

Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic

Bicyclists’ visual strategies when conducting self-paced vs. system-paced smartphone tasks in traffic

Task-Difficulty Homeostasis in Car Following Models: Experimental Validation Using Self-Paced Visual Occlusion

The Tactile Detection Response Task: Preliminary Validation for Measuring the Attentional Effects of Cognitive Load

Contact Info

Product

Resources

About