The effect of three low-cost engineering treatments on driver fatigue: A driving simulator study.

Three engineering treatments were implemented in a driving simulator study to assess the effect of road-based measures on alleviating the symptoms of fatigue. Using results from previous research on the effect of circadian rhythms on fatigue-related crashes, two groups of male drivers were recruited for this study: young shift workers under the age of 35, who attended immediately after their night shift, and older drivers over the age of 45, who completed the study during the 'post lunch dip' period, after consuming lunch. Eye tracking (PERCLOS) and lateral driver performance measures were used to assess whether baseline measures of fatigue changed after drivers experienced each of the three treatments, which included variable message signs, chevrons and rumble strips. Results showed a marked difference in these measures between drivers' baseline (not fatigued) and experimental (fatigued) visits. There were also some reductions in lateral deviation and eye closure (as measured by PERCLOS) when the treatments were encountered, but no marked difference between the three treatments. These results suggest that in addition to driver- and vehicle-based methods currently employed to mitigate the effects of fatigue, the inclusion of such engineering measures may help alleviate fatigue-related impairments in driving, particularly if such treatments are implemented during long stretches of straight monotonous roads which are known to be associated with fatigue-related crashes. However, positive effects of the treatments were short lived, prompting the need for further investigations on their optimal frequency of presentation and combination to achieve maximum impact from these low-cost, road-based treatments.

Control task substitution in semiautomated driving: does it matter what aspects are automated?

OBJECTIVE: The study was designed to show how driver attention to the road scene and engagement of a choice of secondary tasks are affected by the level of automation provided to assist or take over the basic task of vehicle control. It was also designed to investigate the difference between support in longitudinal control and support in lateral control. BACKGROUND: There is comparatively little literature on the implications of automation for drivers' engagement in the driving task and for their willingness to engage in non-driving-related activities. METHOD: A study was carried out on a high-level driving simulator in which drivers experienced three levels of automation: manual driving, semiautomated driving with either longitudinal or lateral control provided, and highly automated driving with both longitudinal and lateral control provided. Drivers were free to pay attention to the roadway and traffic or to engage in a range of entertainment and grooming tasks. RESULTS: Engagement in the nondriving tasks increased from manual to semiautomated driving and increased further with highly automated driving. There were substantial differences in attention to the road and traffic between the two types of semiautomated driving. CONCLUSION: The literature on automation and the various task analyses of driving do not currently help to explain the effects that were found. Lateral support and longitudinal support may be the same in terms of levels of automation but appear to be regarded rather differently by drivers.

Highly automated driving, secondary task performance, and driver state.

OBJECTIVE: A driving simulator study compared the effect of changes in workload on performance in manual and highly automated driving. Changes in driver state were also observed by examining variations in blink patterns. BACKGROUND: With the addition of a greater number of advanced driver assistance systems in vehicles, the driver's role is likely to alter in the future from an operator in manual driving to a supervisor of highly automated cars. Understanding the implications of such advancements on drivers and road safety is important. METHOD: A total of 50 participants were recruited for this study and drove the simulator in both manual and highly automated mode. As well as comparing the effect of adjustments in driving-related workload on performance, the effect of a secondary Twenty Questions Task was also investigated. RESULTS: In the absence of the secondary task, drivers' response to critical incidents was similar in manual and highly automated driving conditions. The worst performance was observed when drivers were required to regain control of driving in the automated mode while distracted by the secondary task. Blink frequency patterns were more consistent for manual than automated driving but were generally suppressed during conditions of high workload. CONCLUSION: Highly automated driving did not have a deleterious effect on driver performance, when attention was not diverted to the distracting secondary task. APPLICATION: As the number of systems implemented in cars increases, an understanding of the implications of such automation on drivers' situation awareness, workload, and ability to remain engaged with the driving task is important.

The effect of stimulus modality on signal detection: implications for assessing the safety of in-vehicle technology.

OBJECTIVE: This study examined the effect of two in-vehicle information systems (IVIS) on signal detection in the visual, auditory, and tactile modalities; established whether the detrimental effects of an IVIS on driving could be quantified by these detection tasks; and examined the effect of stimulus modality on signal detection. BACKGROUND: The peripheral detection task has been used widely for assessing the effects of an IVIS on driving. However, performance on this task relies on drivers' ability to see a series of LEDs, which can be problematic in field tests (e.g., on sunny days). METHOD: Participants responded to one of three detection tasks during a simulated driving experiment. The effect of IVIS interaction on these detection tasks was also measured. Reduced performance in the detection tasks was assumed to indicate a decline in drivers' ability to handle sudden events in the driving task. RESULTS: Response time to all detection tasks increased by around 200 ms when drivers performed the IVIS tasks, as compared with baseline driving. Analyses of variance and comparison of effect sizes showed the effects of these two IVISs to be the same across the three detection tasks. CONCLUSION: These detection tasks are useful for quantifying the safety of an IVIS during driving. The absence of a difference in signal detection by modality suggests that performance on these tasks relies on general attentional resources and is not modality specific. APPLICATION: The signal detection tasks employed here should be further investigated for their suitability in assessing the safety of in-vehicle systems.

Speech-based E-mail and driver behavior: effects of an in-vehicle message system interface.

As mobile office technology becomes more advanced, drivers have increased opportunity to process information "on the move." Although speech-based interfaces can minimize direct interference with driving, the cognitive demands associated with such systems may still cause distraction. We studied the effects on driving performance of an in-vehicle simulated "E-mail" message system; E-mails were either system controlled or driver controlled. A high-fidelity, fixed-base driving simulator was used to test 19 participants on a car-following task. Virtual traffic scenarios varying in driving demand. Drivers compensated for the secondary task by adopting longer headways but showed reduced anticipation of braking requirements and shorter time to collision. Drivers were also less reactive when processing E-mails, demonstrated by a reduction in steering wheel inputs. In most circumstances, there were advantages in providing drivers with control over when E-mails were opened. However, during periods without E-mail interaction in demanding traffic scenarios, drivers showed reduced braking anticipation. This may be a result of increased cognitive costs associated with the decision making process when using a driver-controlled interface when the task of scheduling E-mail acceptance is added to those of driving and E-mail response. Actual or potential applications of this research include the design of speech-based in-vehicle messaging systems.