Measuring working memory load effects on electrophysiological markers of attention orienting during a simulated drive

Effects of background music on numerical and spatial location working memory: differences between extraverts and introverts

This experimental research explored background music's influence on the performance of numerical and spatial location working memory of extraverts and introverts. Sixty participants (30 extraverts and 30 introverts) were asked to complete numerical and spatial location working memory tests, under the conditions of background music and silence. Results showed a main negative effect of background music on the participants' performance of spatial location working memory. A significant interaction effect between music and personality (extroversion and introversion) on this performance was also observed. It revealed that a more negative effect of music in introverts as compared with extroverts. In contrast, no main or interaction effect was observed for the performance of numerical working memory. According to the influence of music on working memory, introversion-extraversion personality factors of workers such as cashiers or drivers require consideration.

On the importance of working memory in the driving safety field: A systematic review

In recent years, many studies have used poor cognitive functions to explain risk safety differences among drivers. Working memory is a cognitive function with information storage and attentional control that plays a crucial role in driver information processing. Furthermore, it is inextricably linked to parameters such as driving performance, driving eye movements and driving neurophysiology, which have a significant impact on drivers' risky behavior and crash risk. In particular, crash risk is a serious risk to social safety and economic development. For this reason, it is necessary to understand how risk-related working memory affects driving so that pre-driving safety pre-training programs and in-vehicle safety assistance systems for driving can be developed accordingly, contributing to the development of semi-autonomous vehicles and even autonomous vehicles. In this paper, a systematic search of the literature over the past 23 years resulted in 78 articles that met the eligibility criteria and quality assessment. The results show that higher working memory capacity, as measured neuropsychologically, is associated with more consistent and safer driving-related parameters for drivers (e.g., lane keeping) and may be related to pupil dilation during risk perception while driving, which is associated with driving outcomes (tickets, pull-overs, penalty points and fines,and driving accidents) is closely related to the perceived usefulness of the human-machine interface, reaction time, standard deviation of steering wheel corners, etc. when the autonomous driving takes over. In addition, higher working memory load interference was associated with more inconsistent and unsafe driving-related parameters (including but not limited to eye movements, electrophysiology, etc.), with higher working memory load being associated with easier driver concentration on the road, faster heart rate, lower heart rate variability, and lower oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). Only a limited number of studies have simultaneously investigated the relationship between working memory capacity, working memory load and driving, showing an interaction between working memory capacity and working memory load on lane change initiation and lane change correctness, with working memory capacity acting as a covariate that mediated the effect of working memory load on braking reaction time. In addition, working memory-related cognitive training had a transfer effect on improving driving ability. Overall, working memory capacity determines the upper limit of the number of working memory attention resources, while working memory load occupies part of the working memory attention resources, thus influencing information perception, decision judgment, operational response, and collision avoidance in driving. Future effective interventions for safe driving can be combined with capacity training and load alerting. These findings contribute to our understanding of the role of working memory in driving and provide new insights into the design of driver safety training programs and automated driving personalized in-vehicle safety systems and roadside devices such as signage.

The Relationship of the Information Quantity of Urban Roadside Traffic Signs and Drivers' Visibility Based on Information Transmission

For the lack of quantitative basis of traffic sign combination information, this paper established a model of information quantity of urban road traffic signs by analyzing the driver’s information processing and the visual recognition of traffic signs combined with theories of informatics. It used various analytical methods to build a model of the relationship between the traffic sign information quantity (TSIQ) and the driver’s visual recognition. Based on factors, the relationship between the TSIQ and the driver’s visual recognition was studied and analyzed to provide a reference for the design of urban traffic sign layout information. The results show that the TSIQ can explain 61% of the driver’s recognition time (DRT). The more information the road traffic sign conveys, the longer DRT will be. The TSIQ’s threshold is 642 bits, and exceeding this value will cause information overload. Different influence factors have a certain impact on drivers’ visual recognition distance (VRD). The male VRD is shorter than the female. The VRD of the young driver is larger than the old driver. The VRD of a novice driver is longer than an experienced driver, while the visual recognition sign of an experienced driver is shorter.

Driving ability in patients with dizziness: a systematic review

PURPOSE

The aim of this systematic review was to identify and evaluate studies dealing with driving performance of dizzy patients or patients with a vestibular disorder.

METHODS

A systematic review was performed according to the preferred reporting items for systematic reviews and meta-analysis guidelines. (1) PubMed, Embase, and Cochrane library. (2) Study selection: articles about driving ability and reported driving difficulties in patients with dizziness, or a diagnosed vestibular disorder, were included. (3) Data extraction was performed by two independent authors using predefined data fields: patient's characteristics, diagnostic criteria, sample size, and type of evaluation of driving ability and outcome of the study.

RESULTS

Eight out of 705 articles matched the inclusion criteria but varied widely regarding the study population, study design, and outcome measures. The majority of studies reported a negative impact of dizziness and/or vestibular disorders on self-reported driving ability and car accidents. Yet several studies could not identify any impairment of driving ability.

CONCLUSIONS

Driving ability was negatively affected by dizziness or a vestibular disorder in the majority of included studies with low risk of bias. This systematic review revealed a significant heterogeneity in studies reporting driving performance and contradictory results. We were, therefore, unable to identify a causal relationship between dizziness and driving ability. There is a need for prospective studies in populations with different vestibular disorders using subjective and objective outcome measures that have been validated to evaluate driving performance.

Low-cost road marking measures for increasing safety in horizontal curves: A driving simulator study

Statistics show that horizontal curves, especially those of radii less than 200 m, present an increased road accident risk mainly due to inappropriate speed and failure to maintain proper lateral position. This simulator study aims to analyse how two low-cost road marking measures (red median and horizontal warning signs), alone or combined with a vertical warning sign, affect driver behaviour (driving speed, lateral movement, acceleration/deceleration) before and throughout dangerous horizontal curves on a two-way rural road. With GIS-supported mapping of traffic accidents, we identified the most dangerous curves on the main rural road in Croatia and replicated them on the driving simulator. Based on the driving runs of 43 participants, the study concluded that both measures, used either alone or combined with a vertical warning sign, significantly reduced the speed compared to the control condition (vertical warning sign alone). Additionally, the use of a red median prompted the lateral movement of the vehicle closer to the edge line. The paper also defines the potential use of the measures for dealing with specific types of curve-related accidents.

Age-Related Changes in Attentional Refocusing during Simulated Driving

We recently reported that refocusing attention between temporal and spatial tasks becomes more difficult with increasing age, which could impair daily activities such as driving (Callaghan et al., 2017). Here, we investigated the extent to which difficulties in refocusing attention extend to naturalistic settings such as simulated driving. A total of 118 participants in five age groups (18–30; 40–49; 50–59; 60–69; 70–91 years) were compared during continuous simulated driving, where they repeatedly switched from braking due to traffic ahead (a spatially focal yet temporally complex task) to reading a motorway road sign (a spatially more distributed task). Sequential-Task (switching) performance was compared to Single-Task performance (road sign only) to calculate age-related switch-costs. Electroencephalography was recorded in 34 participants (17 in the 18–30 and 17 in the 60+ years groups) to explore age-related changes in the neural oscillatory signatures of refocusing attention while driving. We indeed observed age-related impairments in attentional refocusing, evidenced by increased switch-costs in response times and by deficient modulation of theta and alpha frequencies. Our findings highlight virtual reality (VR) and Neuro-VR as important methodologies for future psychological and gerontological research.

Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy

Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level. Using multichannel whole-head high density functional near-infrared spectroscopy (fNIRS) brain activation measurements, we aimed to predict driving difficulty level, both separate for each WML level and with a combined model. Participants drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. In half of the time, the course led through a construction site with reduced lane width, increasing visuospatial attentional demands. Concurrently, participants performed a modified version of the n-back task with five different WML levels (from 0-back up to 4-back), forcing them to continuously update, memorize, and recall the sequence of the previous 'n' speed signs and adjust their speed accordingly. Using multivariate logistic ridge regression, we were able to correctly predict driving difficulty in 75.0% of the signal samples (1.955 Hz sampling rate) across 15 participants in an out-of-sample cross-validation of classifiers trained on fNIRS data separately for each WML level. There was a significant effect of the WML level on the driving difficulty prediction accuracies [range 62.2-87.1%; χ2(4) = 19.9, p < 0.001, Kruskal-Wallis H test] with highest prediction rates at intermediate WML levels. On the contrary, training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46.8%). Activation changes in the bilateral dorsal frontal (putative BA46), bilateral inferior parietal (putative BA39), and left superior parietal (putative BA7) areas were most predictive to increased driving difficulty. These discriminative patterns diminished at higher WML levels indicating that visuospatial attentional demands and WML involve interacting underlying brain processes. The changing pattern of driving difficulty related brain areas across WML levels could indicate potential changes in the multitasking strategy with level of WML demand, in line with the multiple resource theory.