Chasing the silver bullet: measuring driver fatigue using simple and complex tasks

Driver fatigue remains a significant cause of motor-vehicle accidents worldwide. New technologies are increasingly utilised to improve road safety, but there are no effective on-road measures for fatigue. While simulated driving tasks are sensitive, and simple performance tasks have been used in industrial fatigue management systems (FMS) to quantify risk, little is known about the relationship between such measures. Establishing a simple, on-road measure of fatigue, as a fitness-to-drive tool, is an important issue for road safety and accident prevention, particularly as many fatigue related accidents are preventable. This study aimed to measure fatigue-related performance decrements using a simple task (reaction time - RT) and a complex task (driving simulation), and to determine the potential for a link between such measures, thus improving FMS success. Fifteen volunteer participants (7 m, 8 f) aged 22-56 years (mean 33.6 years), underwent 26 h of supervised wakefulness before an 8h recovery sleep opportunity. Participants were tested using a 30-min interactive driving simulation test, bracketed by a 10-min psychomotor vigilance task (PVT) at 4, 8, 18 and 24h of wakefulness, and following recovery sleep. Extended wakefulness caused significant decrements in PVT and driving performance. Although these measures are clearly linked, our analyses suggest that driving simulation cannot be replaced by a simple PVT. Further research is needed to closely examine links between performance measures, and to facilitate accurate management of fitness to drive, which requires more complex assessments of performance than RT alone.     

Effects of chronotype and time of day on the vigilance decrement during simulated driving

The current study tested for the first time the effect of individual differences in circadian rhythmicity (chronotype) on both driving performance and its evolution along time on task. Morning-type and evening-type female participants were tested in morning (8 am) and evening (8 pm) sessions, in which we controlled for prior sleep duration and prior wake. Measures of body temperature, subjective activation and affect, reaction times (RT) in the Psychomotor Vigilance Task (PVT), behavioral performance (error position) and EEG alpha power during simulated driving were collected. The main result showed strong linear increments of mean and standard deviation of error position along time on task (vigilance decrement) when evening-type participants drove at their non-optimal time of day, that is, during the morning session. In contrast, driving performance in the morning-type group remained stable over time on task and was not affected by time of day. This finding can be due to differences in personality traits (e.g., conscientiousness, sensation seeking) and task appraisal associated to extreme chronotypes. The consideration of chronotype in vigilance and driving tasks can enhance safety and human performance by promoting work schedules and countermeasures to prevent failures in the accomplishment of tasks under non-optimal circadian conditions.     

Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation

Drivers are not always aware that they are becoming impaired as a result of sleepiness. Using specific symptoms of sleepiness might assist with recognition of drowsiness related impairment and help drivers judge whether they are safe to drive a vehicle, however this has not been evaluated. In this study, 20 healthy volunteer professional drivers completed two randomized sessions in the laboratory – one under 24 h of acute sleep deprivation, and one with alcohol. The Psychomotor Vigilance Task (PVT) and a 30 min simulated driving task (AusEdTM) were performed every 3–4 h in the sleep deprivation session, and at a BAC of 0.00% and 0.05% in the alcohol session, while electroencephalography (EEG) and eye movements were recorded. After each test session, drivers completed the Karolinska Sleepiness Scale (KSS) and the Sleepiness Symptoms Questionnaire (SSQ), which includes eight specific sleepiness and driving performance symptoms. A second baseline session was completed on a separate day by the professional drivers and in an additional 20 non-professional drivers for test–retest reliability. There was moderate test–retest agreement on the SSQ (r = 0.59). Significant correlations were identified between individual sleepiness symptoms and the KSS score (r values 0.50–0.74, p < 0.01 for all symptoms). The frequency of all SSQ items increased during sleep deprivation (χ² values of 28.4–80.2, p < 0.01 for all symptoms) and symptoms were related to increased subjective sleepiness and performance deterioration. The symptoms “struggling to keep your eyes open”, “difficulty maintaining correct speed”, “reactions were slow” and “head dropping down” were most closely related to increased alpha and theta activity on EEG (r values 0.49–0.59, p < 0.001) and “nodding off to sleep” and “struggling to keep your eyes open” were related to slow eye movements (r values 0.67 and 0.64, p < 0.001). Symptoms related to visual disturbance and impaired driving performance were most accurate at detecting severely impaired driving performance (AUC on ROC curve of 0.86–0.91 for detecting change in lateral lane position greater than the change at a BAC of 0.05%). Individual sleepiness symptoms are related to impairment during acute sleep deprivation and might be able to assist drivers in recognizing their own sleepiness and ability to drive safely.     

Reliability of simulator driving tool for evaluation of sleepiness,fatigue and driving performance

Study objective

To compare the impact of extended wakefulness (i.e., sleepiness) and prolonged driving (i.e., fatigue) at the wheel in simulated versus real-life driving conditions.

Design

Participants drove on an INRETS-MSIS SIM2 simulator in a research laboratory or an open French highway during 3 nocturnal driving sessions. A dose–response design of duration of nocturnal driving was used: a 2 h short driving session (3–5 AM), a 4 h intermediate driving session (1–5 AM) and an 8 h long driving session (9 PM–5 AM).

Participants

Two groups of healthy male drivers (20 for simulated driving and 14 drivers for real driving; mean age ± SD = 22.3 ± 1.6 years), free of sleep disorders.

Measurements

Number of inappropriate line crossings, self-rated fatigue and sleepiness were recorded in the last hour of driving sessions to control the effects of prior waking time and time of day.

Results

Compared to the daytime reference session, both simulated and real driving performance were affected by a short nocturnal driving session (P < .05 and P < .001, respectively). Extension of nocturnal driving duration affected simulated performance nonlinearly and more severely than that of real driving (P < .001).Compared to the daytime reference session, short nocturnal simulated and real driving sessions increased self-perceived fatigue and sleepiness. Real and simulated driving conditions had an identical impact on fatigue and sleepiness during extended periods of nocturnal driving.

Conclusions

In healthy subjects, the INRETS-MSIS SIM2 simulator appropriately measures driving impairment in terms of inappropriate line crossings related to extended wakefulness but has limitations to measure the impact of extended driving on drivers’ performance.     

Risky car following in abstinent users of MDMA

Ecstasy (MDMA) use raises concerns because of its association with risky driving. We evaluated driving performance and risk taking in abstinent recreational MDMA users in a simulated car following task that required continuous attention and vigilance. Drivers were asked to follow two car lengths behind a lead vehicle (LV). Three sinusoids generated unpredictable LV velocity changes. Drivers could mitigate risk by following further behind the erratic LV. From vehicle trajectory data we performed a Fourier analysis to derive measures of coherence, gain, and delay. These measures and headway distance were compared between the different groups. All MDMA drivers met coherence criteria indicating cooperation in the car following task. They matched periodic changes in LV velocity similar to controls (abstinent THC users, abstinent alcohol users, and non-drug users), militating against worse vigilance. While all participants traveled approximately 55 mph (89 kph), the MDMA drivers followed 64 m closer to the LV and demonstrated 1.04 s shorter delays to LV velocity changes than other driver groups. The simulated car following task safely discriminated between driving behavior in abstinent MDMA users and controls. Abstinent MDMA users do not perform worse than controls, but may assume extra risk. The control theory framework used in this study revealed behaviors that might not otherwise be evident.     

The effects of an exercise program on several abilities associated with driving performance in older adults

The purpose of this study was to investigate the effects of participation in an exercise program on several abilities associated with driving performance in older adults. Thirty-two subjects were randomly assigned to either an exercise group (60-81 years, n = 16) or a control group (60-82 years, n = 16). The exercise program was planned to stress perceptive, cognitive, and physical abilities. It lasted 12 weeks with a periodicity of three sessions of 60 min per week. Assessments were conducted before and after the intervention on behavioral speed (in single- and dual-task conditions), visual attention, psychomotor performance, speed perception (time-to-contact), and executive functioning. Significant positive effects were found at 12-week follow-up resulting from participation in the exercise program. Behavioral speed improvements were found in reaction time, movement time, and response time (both in single- and dual-task conditions); visual attention improvements took place in speed processing and divided attention; psychomotor performance improvements occurred in lower limb mobility. These results showed that exercise is capable of enhancing several abilities relevant for driving performance and safety in older adults and, therefore, should be promoted.     

Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves

Driving while sleepy is a serious contributor to automobile accidents. Previous research has shown that drowsy drivers produce systematic errors (variability) in vehicle behavior which are detectable using vehicle monitoring technology. The current study developed a new methodological approach using a vehicle heading difference metric to detect drowsy driving more effectively than other more commonly used methods. Twenty participants completed a driving scenario as well as several measures of fatigue in five testing sessions across a night of sleep deprivation. Each simulated highway driving session lasted 20 min, and was analyzed for lateral lane position variability and vehicle heading difference variability with two statistical methods. Fatigue measures monitored reaction time, attention, and oculomotor movement. The results showed that examining lane heading difference using the absolute value of the raw data detected driving variability better across the night than other statistical models. The results from the fatigue measures indicated an increase in reaction time and response lapses, as well as a decrease in oculomotor reactivity across the night. These results suggest that in fatigued drivers the statistical model using the absolute value of lane heading could be an improved metric for drowsy driving detection that could accurately detect detriments in driving ability at lower levels of fatigue.     

Age differences in cognitive and psychomotor abilities and simulated driving

The current study investigated the relationship between drivers’ abilities in various cognitive and psychomotor domains and their driving performance. The goal was to identify test measures that could be used to develop a fitness-for-driving test battery, particularly for older drivers. Licensed drivers over 40 years of age (M = 65.56 years, SD = 13.02) were recruited from university leisure courses (n = 18) and drivers under 40 (M = 22.20 years, SD = 3.79) were recruited from undergraduate and graduate courses (n = 44). Participants were given a battery of standard neuropsychological tests used to assess ability in the domains of cognitive processing speed, psychomotor functioning, visuospatial performance, sustained attention, and executive functioning. Participants’ driving ability was assessed in a simulator with data collected in three categories of driving performance: (a) driver control maintenance behaviors, (b) accidents and violations, and (c) attention and reaction time. Younger participants outperformed older participants in 4 out of the 5 domains of neuropsychological testing (all but sustained attention). Age differences were found in simulator driving accidents and violations and driving performance was significantly correlated with neuropsychological test performance. The results are discussed in terms of the potential to use these tests to assess older drivers seeking license renewal or for selecting professional drivers for the transportation industry.     

Impaired vigilance and increased accident rate in public transport operators is associated with sleep disorders

Objectives

Sleep disturbances can impair alertness and neurocognitive performance and increase the risk of falling asleep at the wheel. We investigated the prevalence of sleep disorders among public transport operators (PTOs) and assessed the interventional effects on hypersomnolence and neurocognitive function in those diagnosed with obstructive sleep apnea (OSA).

Methods

Overnight polygraphy and questionnaire data from 101 volunteers (72 males, median age 48 range [22–64] years, 87 PTOs) employed at the Gothenburg Public Transportation Company were assessed. Treatment was offered in cases with newly detected OSA. Daytime sleep episodes and neurocognitive function were assessed before and after intervention.

Results

At baseline, symptoms of daytime hypersomnolence, insomnia, restless legs syndrome as well as objectively assessed OSA (apnea hypopnea index (AHI, determined by polygraphic recording) = 17[5–46] n/h) were highly present in 26, 24, 10 and 22%, respectively. A history of work related traffic accident was more prevalent in patients with OSA (59%) compared to those without (37%, p < 0.08). In the intervention group (n = 12) OSA treatment reduced AHI by −23 [−81 to −5] n/h (p = 0.002), determined by polysomnography. Reduction of OSA was associated with a significant reduction of subjective sleepiness and blood pressure. Measures of daytime sleep propensity (microsleep episodes from 9 [0–20.5] to 0 [0–12.5], p < 0.01) and missed responses during performance tests were greatly reduced, indices of sustained attention improved.

Conclusions

PTOs had a high prevalence of sleep disorders, particularly OSA, which demonstrated a higher prevalence of work related accidents. Elimination of OSA led to significant subjective and objective improvements in daytime function. Our findings argue for greater awareness of sleep disorders and associated impacts on daytime function in public transport drivers.     

Short and long sleep duration and risk of drowsy driving and the role of subjective sleep insufficiency

Experimental sleep restriction increases sleepiness and impairs driving performance. However, it is unclear whether short sleep duration in the general population is associated with drowsy driving. The goal of the present study was to evaluate whether individuals in the general population who obtained sleep of 6 h or less are more likely to report drowsy driving, and evaluate the role of perceived sleep sufficiency. Data exploring whether subgroups of short sleepers (those who report the most or least unmet sleep need) show different risk profiles for drowsy driving are limited. From the 2009 Behavioral Risk Factor Surveillance System (N = 31,522), we obtained the following self-reported data: (1) sleep duration (≤5, 6, 7, 8, 9, or ≥10 h/night); (2) number of days/week of perceived insufficient sleep; (3) among drivers, yes/no response to: “During the past 30 days, have you ever nodded off or fallen asleep, even just for a brief moment, while driving?” (4) demographics, physical/mental health. Using 7 h/night as reference, logistic regression analyses evaluated whether self-reported sleep duration was associated with drowsy driving. Overall, 3.6% reported drowsy driving. Self-identified short-sleepers reported drowsy driving more often, and long sleepers, less often. Among those who perceived sleep as always insufficient, drowsy driving was reported more often when sleep duration was ≤5 h, 6 h, or ≥10 h. Among those who perceived sleep as always sufficient, drowsy driving was reported more often among ≤5 h and 6 h sleepers. Overall, drowsy driving was common, particularly in self-identified short-sleepers as a whole, as well as subgroups based on sleep insufficiency.     

A brief peripheral motion contrast threshold test predicts older drivers’ hazardous behaviors in simulated driving

Our research group has previously demonstrated that the peripheral motion contrast threshold (PMCT) test predicts older drivers’ self-report accident risk, as well as simulated driving performance. However, the PMCT is too lengthy to be a part of a battery of tests to assess fitness to drive. Therefore, we have developed a new version of this test, which takes under two minutes to administer. We assessed the motion contrast thresholds of 24 younger drivers (19–32) and 25 older drivers (65–83) with both the PMCT-10 min and the PMCT-2 min test and investigated if thresholds were associated with measures of simulated driving performance. Younger participants had significantly lower motion contrast thresholds than older participants and there were no significant correlations between younger participants’ thresholds and any measures of driving performance. The PMCT-10 min and the PMCT-2 min thresholds of older drivers’ predicted simulated crash risk, as well as the minimum distance of approach to all hazards. This suggests that our tests of motion processing can help predict the risk of collision or near collision in older drivers. Thresholds were also correlated with the total lane deviation time, suggesting a deficiency in processing of peripheral flow and delayed detection of adjacent cars. The PMCT-2 min is an improved version of a previously validated test, and it has the potential to help assess older drivers’ fitness to drive.     

Drivers’ misjudgement of vigilance state during prolonged monotonous daytime driving

To investigate the effects of monotonous daytime driving on vigilance state and particularly the ability to judge this state, a real road driving study was conducted. To objectively assess vigilance state, performance (auditory reaction time) and physiological measures (EEG: alpha spindle rate, P3 amplitude; ECG: heart rate) were recorded continuously. Drivers judged sleepiness, attention to the driving task and monotony retrospectively every 20 min. Results showed that prolonged daytime driving under monotonous conditions leads to a continuous reduction in vigilance. Towards the end of the drive, drivers reported a subjectively improved vigilance state, which was contrary to the continued decrease in vigilance as indicated by all performance and physiological measures. These findings indicate a lack of self-assessment abilities after approximately 3 h of continuous monotonous daytime driving.     

An assessment of the relevance of laboratory and motorcycling tests for investigating time of day and sleep deprivation influences on motorcycling performance

The aim of this study was to assess time of day and sleep deprivation impacts on motorcycling performance taking into consideration key variables, such as reaction time, motor coordination and vigilance that are principally involved in a riding task. Eight subjects participated in different tests sessions planned at 06:00 and 18:00h after a normal night's sleep and after a night of total sleep deprivation. During each session all subjects completed "laboratory" and "motorcycling" tests that were designed to assess each of the variables tested. As classically observed in sport performance, motorcycling performance demonstrates a time of day fluctuation by increasing from 06:00 to 18:00h during the day after a normal night's sleep. For each variable tested, the effects of sleep deprivation depend on the design of the test conditions. Thus, the data collected in laboratory specific conditions are more affected than those noted in arranged motorcycling situations. Taking into account that the sample size used in this study was limited, which may limit the results interpretations, these discrepancies suggest that during complex tasks, compensation mechanisms may be set up between different resources so as to maintain a good level of performance.     

Effects of an afternoon nap on nighttime alertness and performance in long-haul drivers

The effects of an afternoon nap on alertness and psychomotor performance were assessed during a simulated night shift. After a night of partial sleep restriction, eight professional long-haul drivers either slept (nap condition) or engaged in sedentary activities (no-nap condition) from 14:00 to 17:00 h. Alertness and performance testing sessions were conducted at 12:00 (pre-nap baseline), 24:00, 02:30, 05:00 and 07:30 h, and followed 2-h runs in a driving simulator. In the nap condition, the subjects showed lower subjective sleepiness and fatigue, as measured by visual analog scales, and faster reaction times and less variability on psychomotor performance tasks. Electrophysiological indices of arousal during the driving runs also reflected the beneficial effects of the afternoon nap, with lower spectral activity in the theta (4–7.75 Hz), alpha (8–11.75 Hz) and fast theta-slow alpha (6–9.75 Hz) frequency bands of the electroencephalogram, indicating higher arousal levels. Thus, a 3-h napping opportunity ending at 17:00 h improved significantly several indices of alertness and performance measured 7–14 h later.     

How fleeting emotions affect hazard perception and steering while driving: The impact of image arousal and valence

Video-billboards and portable video-display devices are becoming increasingly common and the images they project can often be dramatic or provocative. This study investigated the lingering effects of emotion-evoking images on driving as measured in a driving simulator. Images were projected on an in-vehicle display while drivers followed a lead vehicle at a safe distance. To ensure attention to the images drivers were required to indicate whether each image was positive or negative by pressing a button. Occasional braking events (sudden decelerations in the lead vehicle that necessitated braking) occurred either 250 or 500 ms after the button press. In the 250 ms delay condition braking RT was faster after high arousal images (fastest for high arousal positive images); following a 500 ms delay braking RT was slower after high arousal images (slowest for high arousal negative images). Responding to all images reduced steering performance (in the period after the image but before the button press) but image valence had an effect on steering as well. Positive images were associated with better steering performance than negative images, especially when they were both low in arousal: a result that supports the broaden-and-build hypothesis of positive emotions and the theory that ambient (wide field/peripheral) vision controls steering performance. We discuss implications for both basic research on attention–emotion and applied research on driving.     

Efficient driver drowsiness detection at moderate levels of drowsiness

Previous research on driver drowsiness detection has focused primarily on lane deviation metrics and high levels of fatigue. The present research sought to develop a method for detecting driver drowsiness at more moderate levels of fatigue, well before accident risk is imminent. Eighty-seven different driver drowsiness detection metrics proposed in the literature were evaluated in two simulated shift work studies with high-fidelity simulator driving in a controlled laboratory environment. Twenty-nine participants were subjected to a night shift condition, which resulted in moderate levels of fatigue; 12 participants were in a day shift condition, which served as control. Ten simulated work days in the study design each included four 30-min driving sessions, during which participants drove a standardized scenario of rural highways. Ten straight and uneventful road segments in each driving session were designated to extract the 87 different driving metrics being evaluated. The dimensionality of the overall data set across all participants, all driving sessions and all road segments was reduced with principal component analysis, which revealed that there were two dominant dimensions: measures of steering wheel variability and measures of lateral lane position variability. The latter correlated most with an independent measure of fatigue, namely performance on a psychomotor vigilance test administered prior to each drive. We replicated our findings across eight curved road segments used for validation in each driving session. Furthermore, we showed that lateral lane position variability could be derived from measured changes in steering wheel angle through a transfer function, reflecting how steering wheel movements change vehicle heading in accordance with the forces acting on the vehicle and the road. This is important given that traditional video-based lane tracking technology is prone to data loss when lane markers are missing, when weather conditions are bad, or in darkness. Our research findings indicated that steering wheel variability provides a basis for developing a cost-effective and easy-to-install alternative technology for in-vehicle driver drowsiness detection at moderate levels of fatigue.     

Lorazepam impairs highway driving performance more than heavy alcohol consumption

While research indicates that benzodiazepine (BZD)-like drugs impair driving performance, it remains unclear (i) how far BZDs affect lane-keeping performance, compared with alcohol and (ii) to what extent this impact can realistically be measured in a simulated environment. To clarify these issues, 16 healthy male drivers who had never previously taken BZDs underwent a randomized, crossover, double-blind, placebo-controlled driving paradigm (with the BZD lorazepam) in both real-world and simulated settings. Two lane-keeping variables, namely inappropriate line crossings (ILCs) and standard deviation of lateral position (SDLP), were recorded during the driving sessions. Analyses revealed that (i) a single lorazepam dose (2 mg given by mouth) caused higher SDLP increases than a blood alcohol concentration of above 0.05%, and that (ii) this BZD effect was amplified in the simulated driving setting, mainly for ILCs. As a consequence, we recommend that physicians be made more aware of BZD-related risks and that researchers make a clear distinction between the effects of BZD intake per se and the impact of simulated driving settings.     

Fatigue, sleep restriction and driving performance

We ran a randomized cross-over design study under sleep-deprived and non-sleep-deprived driving conditions to test the effects of sleep restriction on real driving performance. The study was performed in a sleep laboratory and on an open French highway. Twenty-two healthy male subjects (age = 21.5 +/- 2 years; distance driven per year = 12,225 +/- 4739 km (7641 +/- 2962 miles) [mean +/- S.D.]) drove 1000 km (625 miles) over 10 h during five 105 min sessions on an open highway. Self-rated fatigue and sleepiness before each session, number of inappropriate line crossings from video recordings and simple reaction time (RT) were measured. Total crossings increased after sleep restriction (535 crossings in the sleep-restricted condition versus 66 after non-restricted sleep (incidence rate ratio (IRR): 8.1; 95% confidence interval (95% CI): 3.2-20.5; p < 0.001)), from the first driving session. The interaction between the two factors (conditionxtime of day) was also significant (F(5, 105) = 3.229; p < 0.05). Increasing sleepiness score was associated with increasing crossings during the next driving session in the sleep-restricted (IRR: 1.9; 95% CI: 1.4-2.4) but not in the non-restricted condition (IRR: 1.0; 95% CI: 0.8-1.3). Increasing self-perceived fatigue was not associated with increasing crossings in either condition (IRR: 0.95; 95% CI: 0.93-0.98 and IRR: 1.0; 95% CI: 0.98-1.02). Rested subjects drove 1000 km with four shorts breaks with only a minor performance decrease. Sleep restriction induced important performance degradation even though time awake (8h) and session driving times (105 min) were relatively short. Major inter-individual differences were observed under sleep restriction. Performance degradation was associated with sleepiness and not fatigue. Sleepiness combined with fatigue significantly affected RT. Road safety campaigns should encourage drivers to avoid driving after sleep restriction, even on relatively short trips especially if they feel sleepy.     

Does attention capacity moderate the effect of driver distraction in older drivers?

With age, a decline in attention capacity may occur and this may impact driving performance especially while distracted. Although the effect of distraction on driving performance of older drivers has been investigated, the moderating effect of attention capacity on driving performance during distraction has not been investigated yet. Therefore, the aim was to investigate whether attention capacity has a moderating effect on older drivers’ driving performance during visual distraction (experiment 1) and cognitive distraction (experiment 2). In a fixed-based driving simulator, older drivers completed a driving task without and with visual distraction (experiment 1, N = 17, mean age 78 years) or cognitive distraction (experiment 2, N = 35, mean age 76 years). Several specific driving measures of varying complexity (i.e., speed, lane keeping, following distance, braking behavior, and crashes) were investigated. In addition to these objective driving measures, subjective measures of workload and driving performance were also included. In experiment 1, crash occurrence increased with visual distraction and was negatively related to attention capacity. In experiment 2, complete stops at stop signs decreased, initiation of braking at pedestrian crossings was later, and crash occurrence increased with cognitive distraction. Interestingly, for a measure of lane keeping (i.e., standard deviation of lateral lane position (SDLP)), effects of both types of distraction were moderated by attention capacity. Despite the decrease of driving performance with distraction, participants estimated their driving performance during distraction as good. These results imply that attention capacity is important for driving. Driver assessment and training programs might therefore focus on attention capacity. Nonetheless, it is crucial to eliminate driver distraction as much as possible given the deterioration of performance on several driving measures in those with low and high attention capacity.     

Brake lamp detection in complex and dynamic environments: Recognizing limitations of visual attention and perception

Worldwide, both brake lamps and tail lamps on motor vehicles are required to be red. Previous studies have not examined the effect of this confound in a complex, high-traffic scenario in a driving simulator or on visuomotor behavior. In the first experiment, drivers detected brake lamps on nine lead vehicles and lane changes on two rear vehicles in a 15 min simulated night time highway drive. A second experiment was used to examine the findings in the context of pre-attentive visual processing research. A third experiment analyzed visuomotor behavior and subjective workload during a vigilance task to further evaluate this hypothesis. For all studies, tail lamp color was manipulated, resulting in two conditions: the currently mandated red tail lamps and red brake lamps vs. yellow tail lamps and red brake lamps. Compared to current rear lighting, employing yellow tail lamps with red brake lamps reduced RT, error, subjective workload, improved performance in detecting lane changes and also changed visuomotor behavior. It is suggested that the mechanism allowing better performance is pre-attentive, parallel visual processing.