Jason S. McCarley

Lane Keeping Under Cognitive Load Performance Changes and Mechanisms

Objective: A pair of simulated driving experiments studied the effects of cognitive load on drivers’ lane-keeping performance. Background: Cognitive load while driving often reduces the variability of lane position. However, there is no agreement as to whether this effect should be interpreted as a performance loss, consistent with other effects of distraction on driving, or as an anomalous performance gain. Method: Participants in a high-fidelity driving simulator performed a lane-keeping task in lateral wind, with instructions to keep a steady lane position. Under high load conditions, participants performed a concurrent working memory task with auditory stimuli. Cross-spectral analysis measured the relationship between wind force and steering inputs. Results: Cognitive load reduced the variability of lane position and increased the coupling between steering wheel position and crosswind strength. Conclusion: Although cognitive load disrupts driver performance in a variety of ways, it produces a performance gain in lane keeping. This effect appears to reflect drivers’ efforts to protect lateral control against the risk of distraction, at the apparent neglect of other elements of driving performance. Application: Results may inform educational efforts to help drivers understand the risks of distraction and the inadequacies of compensatory driving strategies.

Texting while driving using google glass: Promising but not distraction-free

Texting while driving is risky but common. This study evaluated how texting using a Head-Mounted Display, Google Glass, impacts driving performance. Experienced drivers performed a classic car-following task while using three different interfaces to text: fully manual interaction with a head-down smartphone, vocal interaction with a smartphone, and vocal interaction with Google Glass. Fully manual interaction produced worse driving performance than either of the other interaction methods, leading to more lane excursions and variable vehicle control, and higher workload. Compared to texting vocally with a smartphone, texting using Google Glass produced fewer lane excursions, more braking responses, and lower workload. All forms of texting impaired driving performance compared to undistracted driving. These results imply that the use of Google Glass for texting impairs driving, but its Head-Mounted Display configuration and speech recognition technology may be safer than texting using a smartphone.

Metacognition of multitasking: How well do we predict the costs of divided attention?

Risky multitasking, such as texting while driving, may occur because people misestimate the costs of divided attention. In two experiments, participants performed a computerized visual-manual tracking task in which they attempted to keep a mouse cursor within a small target that moved erratically around a circular track. They then separately performed an auditory n-back task. After practicing both tasks separately, participants received feedback on their single-task tracking performance and predicted their dual-task tracking performance before finally performing the 2 tasks simultaneously. Most participants correctly predicted reductions in tracking performance under dual-task conditions, with a majority overestimating the costs of dual-tasking. However, the between-subjects correlation between predicted and actual performance decrements was near 0. This combination of results suggests that people do anticipate costs of multitasking, but have little metacognitive insight on the extent to which they are personally vulnerable to the risks of divided attention, relative to other people.

Age, clutter, and competitive selection

Modern theory explains visual selective attention as a competition for receptive fields in the extrastriate cortex. The present study examined whether this competition contributes to older adults difficulty in processing visual clutter. In 2 experiments, young and older adult subjects made same-different judgments of target shapes in displays with or without clutter. The target shapes were either high or low in discriminability. The spatial separation between targets varied across trials, and the effects of competitive selection were gauged through decrements in task performance that resulted as separation decreased. Both age groups showed a competition-in-clutter effect, evincing a stronger influence of target separation within cluttered displays. However, the costs of clutter in general and the strength of the competition-in-clutter effect more specifically were both substantially larger for older adults. Effects of clutter and competition also varied with stimulus discriminability; judgments of highly discriminable stimuli evinced no intertarget competition in uncluttered displays for either age group, while judgments of less discriminable stimuli showed competition whether clutter was present or not. Results suggest that clutter disproportionately degrades older adults visual performance by forcing more careful stimulus resolution, engendering stronger competition for selection.

Change Detection: Training and Transfer

Observers often fail to notice even dramatic changes to their environment, a phenomenon known as change blindness. If training could enhance change detection performance in general, then it might help to remedy some real-world consequences of change blindness (e.g. failing to detect hazards while driving). We examined whether adaptive training on a simple change detection task could improve the ability to detect changes in untrained tasks for young and older adults. Consistent with an effective training procedure, both young and older adults were better able to detect changes to trained objects following training. However, neither group showed differential improvement on untrained change detection tasks when compared to active control groups. Change detection training led to improvements on the trained task but did not generalize to other change detection tasks.

Effects of Age on Utilization and Perceived Reliability of an Automated Decision-Making aid for Luggage Screening

An experiment examined the effects of age on utilization and perceived reliability of an imperfectly reliable decision-making aid in a luggage x-ray screening task. Forty-five young adults and 45 elderly adults performed a simulated luggage screening task. Some subjects were provided the assistance of an automated decision aid with a hit rate of .90 and a false alarm rate of .25. Others performed the task with no aid. Signal-detection analysis revealed that automation improved sensitivity only for younger participants, suggesting a tendency for older participants to underutilize the aids recommendations. Data also revealed unique patterns of individual differences in cue reliance among older and younger participants. Perceived reliability of the aid did not differ between age groups. Order of information presentation (with the aids recommendation coming before or after the raw data) had little effect for either age group.

N-SEEV: A Computational Model of Attention and Noticing

The N-SEEV is a stochastic model of overt attention within a visual display or workspace. The model integrates elements from several existing models of attention (Bundesen, 1987, 1990; Itti & Koch, 2000; Wolfe, 1994; Wickens, et al., 2003) to provide (1) predictions of the allocation of visual attention among discrete display channels; (2) the likelihood of a scanning transition between any pair of channels; and (3) the number of eye movements needed to fixate the onset of a visual signal or event. Preliminary tests of the model show a close fit between model predictions and actual pilot scanning and noticing times.

The Harder the Task, the More Inconsistent the Performance: A PPT Analysis on Task Difficulty

ABSTRACT Previous research has demonstrated that as task difficulty increases, task performance subsequently decreases. These decrements in task performance as difficulty increases have been attributed to the processes individuals use to complete tasks. Over a series of three experiments, Potential Performance Theory (PPT; Trafimow & Rice, 2008; 2009), was used to test the hypothesis that decreases in task performance are, in part, due to inconsistency rather than only systematic factors. Task difficulty was manipulated in three visual search tasks by increasing set size (Experiment 1), decreasing contrast (Experiment 2), and increasing background distracters (Experiment 3). Findings over the three studies indicated that decreases in observed task performance as task difficulty increases are primarily due to a decrease of consistency rather than systematic factors. The theoretical implications of these findings are discussed.

Spatial interference between attended items engenders serial visual processing

A pair of experiments investigated the architecture of visual processing, parallel versus serial, across high and low levels of spatial interference in a divided attention task. Subjects made speeded judgments that required them to attend to a pair of color-cued objects among gray filler items, with the spatial proximity between the attended items varied to manipulate the strength of interference between attended items. Systems factorial analysis (Townsend & Nozawa, Journal of Mathematical Psychology 39:321-359, 1995) was used to identify processing architecture. Experiment 1, using moderately dense displays, found evidence of parallel processing whether attended objects were in low or high proximity to one another. Experiment 2, using higher-density displays, found evidence of parallel selection when attended stimuli were widely separated but serial processing when they were in high proximity. Divided visual attention can operate in parallel under conditions of low or moderate spatial interference between selected items, but strong interference engenders serial processing.

Do wearable devices bring distraction closer to the driver? Comparing smartphones and Google Glass

BACKGROUNDnHead-up and wearable displays, such as Google Glass™, are sometimes marketed as safe in-vehicle alternatives to phone-based displays, as they allow drivers to receive messages without eye-off-the-road glances. However, head-up displays can still compromise driver performance (e.g., He et al., 2015b), as the distracting effect of interacting with any device will depend on the users multitasking strategies. The present experiment examined drivers interaction with a head-down smartphone display and a wearable head-up display.nnnMETHODnParticipants performed a simulated driving task while receiving and responding to text messages via smartphone or the head-mounted display (HMD) on the Google Glass™. Incoming messages were signaled by an auditory alert, and responses were made vocally.nnnRESULTSnWhen using Google Glass, participants responses were quicker than that of smartphone, and the time to engage in a task did not vary according to lane-keeping difficulty. Results suggest that a willingness to engage more readily in distracting tasks may offset the potential safety benefits of wearable devices.