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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Detection Response Tasks: Using Remote, Headmounted and Tactile Signals to Assess Cognitive Demand While Driving</title>
      <link>https://trid.trb.org/View/1261938</link>
      <description><![CDATA[Three versions of the Detection Response Task (DRT) were evaluated and compared as methods to assess cognitive demand while driving. Participants performed tasks known to manipulate cognitive demand (N_Back tasks) and real-world cognitive demand tasks using the iPhone interface, Siri, while driving a simulator. The Remote DRT, the Head Mounted DRT and the Tactile DRT were all sensitive to task demands but advantages were found to using the newer versions for the assessment of cognitive distraction. This work is part of an international collaborative research effort to standardize the DRT (ISO WD17488).]]></description>
      <pubDate>Fri, 20 Sep 2013 09:54:41 GMT</pubDate>
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      <title>Impact of age and cognitive demand on lane choice and changing under actual highway conditions</title>
      <link>https://trid.trb.org/View/1247533</link>
      <description><![CDATA[Previous research suggests that drivers change lanes less frequently during periods of heightened cognitive load. However, lane changing behavior of different age groups under varying levels of cognitive demand is not well understood. The majority of studies which have evaluated lane changing behavior under cognitive workload have been conducted in driving simulators. Consequently, it is unclear if the patterns observed in these simulation studies carry over to actual driving. This paper evaluates data from an on-road study to determine the effects of age and cognitive demand on lane choice and lane changing behavior. Three age groups (20–29, 40–49, and 60–69) were monitored in an instrumented vehicle. The 40s age group had 147% higher odds of exhibiting a lane change than the 60s group. In addition, drivers in their 60's were less likely to drive on the leftmost lane compared to drivers in their 20s and 40s. These results could be interpreted as evidence that older adults adopt a more conservative driving style as reflected in being less likely to choose the leftmost lane than the younger groups and less likely to change lanes than drivers in their 40s. Regardless of demand level, cognitive workload reduced the frequency of lane changes for all age groups. This suggests that in general drivers of all ages attempt to regulate their behavior in a risk reducing direction when under added cognitive demand. The extent to which such self-regulation fully compensates for the impact of added cognitive demand remains an open question.]]></description>
      <pubDate>Tue, 30 Apr 2013 16:07:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/1247533</guid>
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      <title>Daydream perceiver</title>
      <link>https://trid.trb.org/View/1143240</link>
      <description><![CDATA[This article presents the latest research from the Massachusetts Institute of Technology (MIT) regarding the distraction to drivers caused by cognitive activities. While much of the research over the past 20-plus years has focused on tasks that require drivers to take their eyes off the road or hands away from the steering wheel, categorized as visual and manual demands, it would be incomplete not to take into account the full range of cognitive, visual and manipulative activities that are required for safe operation. Examples of this include hands-free conversations and voice interactions. Experts at MIT seek to answer the question, at what level of cognitive demand do drivers' minds become distracted to the point that they lose situational awareness to respond adequately to changing roadway demands? Various studies are presented to explore the answers to this questions, and one interesting result was that patterns of visual scanning remained the same across all age brackets. This research holds relevance as it is important to develop a method for safely and effectively alerting the driver as technology moves towards autonomous vehicles in the future.]]></description>
      <pubDate>Wed, 18 Jul 2012 16:13:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1143240</guid>
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      <title>Effects on Eye-Fixation-Related Potential of a Driver's Conversation and Visual Search</title>
      <link>https://trid.trb.org/View/1106691</link>
      <description><![CDATA[This paper describes the effects of a driver’s conversation and visual search on eye-fixation-related potential (EFRP). Experiments are conducted with a driving simulator. Electroencephalogram (EEG) is performed when the participants were assigned a driving task and a cognitive task concurrently. Cognitive tasks include conversation, visual search, and manipulation of a mobile phone. EFRP is calculated by averaging the EEG waves whose offsets are determined by saccadic eye movements. The amplitude of the EFRP signal is used for estimating the level of a driver’s distraction. The results show that the amplitude of lambda response in EFRP decreases when considerable attention is required to execute a cognitive task. Simulation results using the obtained ERRP data are also discussed.]]></description>
      <pubDate>Thu, 21 Jul 2011 10:07:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1106691</guid>
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      <title>R We Fooling Ourselves: Does the Occlusion Technique Shortchange R Estimates?</title>
      <link>https://trid.trb.org/View/814436</link>
      <description><![CDATA[The occlusion technique was originally used to evaluate the cognitive demands of the roadway. Recently, the occlusion technique has been used as a cost-effective tool for assessing the visual demand of in-vehicle devices. Occlusions simulate glances from an in-vehicle device to the roadway by interrupting visual sampling. However, occluding the in-vehicle device does not impose any additional cognitive demand on the participant like true glances back to the roadway. The purpose of this study was to compare standard no-task occlusions with occlusions requiring participants to perform a visual-motor tracking task. Results suggest that overestimates of resumability may result by not including a task during occlusions. Furthermore, estimations of visual demand based on individual post-occlusion resumption times may provide a more precise measure of transition costs and resumability than measures based on Total Shutter Open Time.]]></description>
      <pubDate>Thu, 23 Aug 2007 13:01:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/814436</guid>
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    <item>
      <title>Modeling Cognitive Complexity in Air Traffic Control</title>
      <link>https://trid.trb.org/View/781600</link>
      <description><![CDATA[Eurocontrol has constructed a model of traffic complexity that tries to better incorporate the cognitive aspects of air traffic control.   Air traffic complexity is aspects of traffic patterns that evaluate air traffic control productivity, benchmarking, cost effectiveness and contribute to an air traffic controller's workload.  The COmplexity and CApacity project (COCA) of Eurocontrols's attempts to build a model of air traffic complexity, apply the complexity model, build a model of sector capacity and apply the model to sector classification. The authors discover that no single indicator of air traffic complexity applies equally well, and that the controller perceives that no current geometric approach incorporates the complexity involved in air traffic control.]]></description>
      <pubDate>Wed, 31 May 2006 09:31:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/781600</guid>
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      <title>THE INFLUENCE OF COGNITION AND AGE ON ACCOMMODATION, DETECTION RATE AND RESPONSE TIMES WHEN USING A CAR HEAD-UP DISPLAY (HUD)</title>
      <link>https://trid.trb.org/View/505646</link>
      <description><![CDATA[Car head-up displays (HUDs), which portray information in the form of a virtual image reflected off a combiner, allow the viewing of complex information, such as route guidance, without the need for the driver to look away from the road ahead.  The cognitive demand required by the HUD task may distract drivers from the outside world scene and cause reaction times to slow. Cognitive capacity also decreases with age.  The aim of the present study was to determine the effect of cognitive demand and age on the use of a car HUD.  Subjects (young, middle or older age drivers, each group n=8) performed a HUD-assisted driving task, with three levels of cognitive demand, whilst accommodation was simultaneously measured using a dynamically recording infra-red optometer.  Response times to, and the detection rate of, changes in both the HUD image and the outside world scene were analyzed.  Increasing the cognitive demand associated with the HUD image increased over-accommodation (greatest in the young, 0.34 + or - 0.05 D, p<0.001).  Response times to and detection of changes in the HUD image and outside world scene were significantly worse with increased cognitive demand.  Response times to and detection of changes in the HUD image and outside world scene also increased with age.  The implication of the results with respect to car HUD design and safety are discussed.]]></description>
      <pubDate>Mon, 23 Aug 1999 00:00:00 GMT</pubDate>
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