Driver Expectations of a Partial Driving Automation System in Relation to Branding and Training

OBJECTIVE

The current study examined whether differences in the branding and description or mode of training materials influence drivers' understanding and expectations of a partial driving automation system.

BACKGROUND

How technology is described might influence consumers' understanding and expectations, even if all information is accurate.

METHOD

Ninety drivers received training about a real partial driving automation system with a fictitious name. Participants were randomly assigned to a branding condition (system named AutonoDrive, training emphasized capabilities; or system named DriveAssist, training emphasized limitations) and training mode (quick-start brochure; video; or in-person demonstration). No safety-critical information was withheld nor deliberately misleading information provided. After training, participants drove a vehicle equipped with the system. Associations of drivers' expectations with branding condition and training mode were assessed using between-subjects comparisons of questionnaire responses obtained pre- and post-drive.

RESULTS

Immediately after training, those who received information emphasizing the system's capabilities had greater expectations of the system's function and crash avoidance capability in a variety of driving scenarios, including many in which the system would not work, as well as greater willingness to utilize the system's workload reduction benefits to take more risks. Most but not all differences persisted after driving the vehicle. Expectations about collision avoidance differed by training mode pre-drive but not post-drive.

CONCLUSION

Training that emphasizes a partial driving automation system's capabilities and downplays its limitations can foster overconfidence.

APPLICATION

Accuracy of technical information does not guarantee understanding; training should provide a balanced view of a system's limitations as well as capabilities.

Preface to the Special Issue on Assessment and Effectiveness of Driver Monitoring Systems

With vehicle automation becoming more commonplace, the role of the human driver is shifting from that of system operator to that of system supervisor. With this shift comes the risk of drivers becoming more disengaged from the task of supervising the system functioning, thus increasing the need for technology to keep drivers alert. This special issue includes the most up-to-date research on how drivers use vehicle automation, and the safety risks it may pose. It also investigates the accuracy that driver monitoring systems have in detecting conditions like driver distraction and drowsiness, and explores ways future drivers may respond to the broader introduction of this technology on passenger vehicles.

Feeling sleepy? stop driving-awareness of fall asleep crashes

STUDY OBJECTIVES

To examine whether drivers are aware of sleepiness and associated symptoms, and how subjective reports predict driving impairment and physiological drowsiness.

METHODS

Sixteen shift workers (19-65 years; 9 women) drove an instrumented vehicle for 2 hours on a closed-loop track after a night of sleep and a night of work. Subjective sleepiness/symptoms were rated every 15 minutes. Severe and moderate driving impairment was defined by emergency brake maneuvers and lane deviations, respectively. Physiological drowsiness was defined by eye closures (Johns drowsiness scores) and EEG-based microsleep events.

RESULTS

All subjective ratings increased post night-shift (p < 0.001). No severe drive events occurred without noticeable symptoms beforehand. All subjective sleepiness ratings, and specific symptoms, predicted a severe (emergency brake) driving event occurring in the next 15 minutes (OR: 1.76-2.4, AUC > 0.81, p < 0.009), except "head dropping down". Karolinska Sleepiness Scale (KSS), ocular symptoms, difficulty keeping to center of the road, and nodding off to sleep, were associated with a lane deviation in the next 15 minutes (OR: 1.17-1.24, p<0.029), although accuracy was only "fair" (AUC 0.59-0.65). All sleepiness ratings predicted severe ocular-based drowsiness (OR: 1.30-2.81, p < 0.001), with very good-to-excellent accuracy (AUC > 0.8), while moderate ocular-based drowsiness was predicted with fair-to-good accuracy (AUC > 0.62). KSS, likelihood of falling asleep, ocular symptoms, and "nodding off" predicted microsleep events, with fair-to-good accuracy (AUC 0.65-0.73).

CONCLUSIONS

Drivers are aware of sleepiness, and many self-reported sleepiness symptoms predicted subsequent driving impairment/physiological drowsiness. Drivers should self-assess a wide range of sleepiness symptoms and stop driving when these occur to reduce the escalating risk of road crashes due to drowsiness.

Frequency and Quality of Exposure to Adaptive Cruise Control and Impact on Trust, Workload, and Mental Models

Advanced Driver Assistance Systems (ADAS) support drivers with some driving tasks. However, drivers may lack appropriate knowledge about ADAS resulting in inadequate mental models. This may result in drivers misusing ADAS, or mistrusting the technologies, especially after encountering edge-case events (situations beyond the capability of an ADAS where the system may malfunction or fail) and may also adversely affect driver workload. Literature suggests mental models could be improved through exposure to ADAS-related driving situations, especially those related to ADAS capabilities and limitations. The objective of this study was to examine the impact of frequency and quality of exposure on drivers' understanding of Adaptive Cruise Control (ACC), their trust, and their workload after driving with ACC. Sixteen novice ACC users were recruited for this longitudinal driving simulator study. Drivers were randomly assigned to one of two groups - the 'Regular Exposure' group encountering 'routine' edge-case events, and the 'Enhanced Exposure' group encountering 'routine' and 'rare' events. Each participant undertook four different simulator sessions, each separated by about a week. Each session comprised a simulator drive featuring five edge-case scenarios. The study followed a mixed-subject design, with exposure frequency as the within-subject variable, and quality of exposure (defined by two groups) as the between-subject variable. Surveys measured drivers' trust, workload, and mental models. The results from the analyses using linear regression models revealed that drivers' mental models about ACC improve with frequency of exposure to ACC and associated edge-case driving situations. This was more the case for drivers who experienced 'rare' ACC edge cases. The findings also indicate that for those who encountered 'rare' edge cases, workload was higher and trust was lower than those who did not. These findings are significant since they underline the importance of experience and familiarity with ADAS for safe operation. While these findings indicate that drivers benefit from increased exposure to ACC and edge cases in terms of appropriate use of ADAS, and ultimately promise crash reductions and injury prevention, a challenge remains regarding how to provide drivers with appropriate exposure in a safe manner.

Minding the Gap: Effects of an Attention Maintenance Training Program on Driver Calibration

OBJECTIVE

The present study examines the effect of an existing driver training program, FOrward Concentration and Attention Learning (FOCAL) on young drivers' calibration, drivers' ability to estimate the length of their in-vehicle glances while driving, using two different measures, normalized difference scores and Brier Scores.

BACKGROUND

Young drivers are poor at maintaining attention to the forward roadway while driving a vehicle. Additionally, drivers may overestimate their attention maintenance abilities. Driver training programs such as FOCAL may train target skills such as attention maintenance but also might serve as a promising way to reduce errors in drivers' calibration of their self-perceived attention maintenance behaviors in comparison to their actual performance.

METHOD

Thirty-six participants completed either FOCAL or a Placebo training program, immediately followed by driving simulator evaluations of their attention maintenance performance. In the evaluation drive, participants navigated four driving simulator scenarios during which their eyes were tracked. In each scenario, participants performed a map task on a tablet simulating an in-vehicle infotainment system.

RESULTS

FOCAL-trained drivers maintained their attention to the forward roadway more and reported better calibration using the normalized difference measure than Placebo-trained drivers. However, the Brier scores did not distinguish the two groups on their calibration.

CONCLUSION

The study implies that FOCAL has the potential to improve not only attention maintenance skills but also calibration of the skills for young drivers.

APPLICATION

Driver training programs may be designed to train not only targeted higher cognitive skills but also driver calibration-both critical for driving safety in young drivers.

Fatal hit-and-run crashes: Factors associated with leaving the scene

INTRODUCTION

Hit-and-run crashes are a criminal offense that leave the victim without prompt medical care or the ability to receive financial compensation.

METHOD

The purpose of the current study was to quantify the factors associated with the probability that a driver leaves the scene of a fatal crash, using multiple imputation to incorporate information from drivers who were never apprehended and thus whose characteristics were unknown.

RESULTS

The results of this study show that in addition to driver, vehicle, and environmental factors having significant impacts on the likelihood of a driver fleeing the scene, economic and demographic factors are important as well. Practical Applications: This analysis allows for a more holistic understanding of hit-and-run crashes and informs potential countermeasures and future research.

Investigating the impact of driving automation systems on distracted driving behaviors

Driving automation systems (e.g., SAE Level 2) ultimately aim to enhance the comfort and safety of drivers. At present, these systems are able to control some portions of the driving task (e.g., braking, steering) for extended time periods, giving drivers the opportunity to disengage from the responsibilities associated with driving. In this study, data derived from two naturalistic driving studies involving automation-equipped vehicles were analyzed to evaluate driver behaviors with respect to driving automation system use, specifically distraction-related factors (i.e., secondary task engagement, eye-glance behavior, and drowsiness). The results indicate that when drivers had prior experience using driving automation systems, they were almost two times as likely to participate in distracted driving behaviors when the systems were active than during manual driving. Drivers with less experience and familiarity with driving automation systems were less likely to drive distracted when the systems were active; however, these drivers tended to be somewhat drowsy when driving with systems activated. The results provide important insights into different operational phases of driving automation system use (i.e., learning/unfamiliar vs experienced users), whereby experience results in overtrust and overreliance on the advanced technologies, which subsequently may negate some of the safety benefits of these systems. Thus, while the safety benefits of driving automation systems are evident, it is imperative to better understand the impact these advanced technologies may have on driver behavior and performance in order to evaluate and address any unintended consequences associated with system use.

Age-Related Differences in the Cognitive, Visual, and Temporal Demands of In-Vehicle Information Systems

In-vehicle information systems (IVIS) refer to a collection of features in vehicles that allow motorists to complete tasks (often unrelated to driving) while operating the vehicle. These systems may interfere, to a greater extent, with older drivers' ability to attend to the visual and cognitive demands of the driving environment. The current study sought to examine age-related differences in the visual, cognitive and temporal demands associated with IVIS interactions. Older and younger drivers completed a set of common tasks using the IVIS of a representative sample of six different vehicles while they drove along a low-density residential street. Evaluation measures included a Detection Response Task (DRT), to assess both cognitive and visual attention, and subjective measures following each condition using the NASA Task Load Index (TLX). Two age cohorts were evaluated: younger drivers between 21 and 36 years of age, and older drivers between 55 and 75 years of age. Participants completed experimental tasks involving interactions with the IVIS to achieve a specific goal (i.e., using the touch screen to tune the radio to a station; using voice commands to find a specified navigation destination, etc.). Performance of tasks varied according to different modes of interaction available in the vehicles. Older drivers took longer to complete tasks, were slower to react to stimuli, and reported higher task demand when interacting with IVIS. Older drivers stand to benefit the most from advancements in-vehicle technology, but ironically may struggle the most to use them. The results document significant age-related costs in the potential for distraction from IVIS interactions on the road.

The Relationship between in-Vehicle Technologies and Self-Regulation among Older Drivers

The study sought to understand the relationship between in-vehicle technologies (IVTs) and self-regulatory behaviors among older drivers. In a large multi-site study of 2990 older drivers, self-reported data on the presence of IVTs and avoidance of various driving behaviors (talking on a mobile phone while driving, driving at night, driving in bad weather, and making left turns when there is no left turn arrow) were recorded. Self-reports were used to identify whether avoidance was due to self-regulation. Hierarchical logistic regressions were used to determine whether the presence of a particular IVT predicted the likelihood of a given self-regulatory behavior after controlling for other factors. Results suggest that the presence of Integrated Bluetooth/Voice Control systems are related to a reduced likelihood of avoiding talking on a mobile phone while driving due to self-regulation (OR= 0.37, 95% CI= 0.29-0.47). The presence of a Navigation Assistance system was related to a reduced likelihood of avoiding talking on a mobile phone while driving (OR= 0.65, 95% CI= 0.50-0.84) and avoiding driving at night due to self-regulation (OR= 0.80, 95% CI = 0.64-1.00). Present findings suggest in-vehicle technologies may differently influence the self-regulatory behaviors of older drivers.

Preface to the Special Issue on Human Factors and Advanced Vehicle Automation: Of Benefits, Barriers, and Bridges to Safe and Effective Implementation

OBJECTIVE

The aim of this special issue is to bring together the latest research related to driver interaction with various types of vehicle automation.

BACKGROUND

Vehicle technology has undergone significant progress over the past decade, bringing new support features that can assist the driver and take on more and more of the driving responsibilities.

METHOD

This issue is comprised of eight articles from international research teams, focusing on different types of automation and different user populations, including driver support features through to highly automated driving systems.

RESULTS

The papers comprising this special issue are clustered into three categories: (a) experimental studies of driver interactions with advanced vehicle technologies; (b) analysis of existing data sources; and (c) emerging human factors issues. Studies of currently available and pending systems highlight some of the human factors challenges associated with the driver-system interaction that are likely to become more prominent in the near future. Moreover, studies of more nascent concepts (i.e., those that are still a long way from production vehicles) underscore many attitudes, perceptions, and concerns that will need to be considered as these technologies progress.

CONCLUSIONS

Collectively, the papers comprising this special issue help fill some gaps in our knowledge. More importantly, they continue to help us identify and articulate some of the important and potential human factors barriers, design considerations, and research needs as these technologies become more ubiquitous.

Detection of driver manual distraction via image-based hand and ear recognition

Driving distraction is a leading cause of fatal car accidents, and almost nine people are killed in the US each day because of distracting activities. Therefore, reducing the number of distraction-affected traffic accidents remains an imperative issue. A novel algorithm for detection of drivers' manual distraction was proposed in this manuscript. The detection algorithm consists of two modules. The first module predicts the bounding boxes of the driver's right hand and right ear from RGB images. The second module takes the bounding boxes as input and predicts the type of distraction. 106,677 frames extracted from videos, which were collected from twenty participants in a driving simulator, were used for training (50%) and testing (50%). For distraction classification, the results indicated that the proposed framework could detect normal driving, using the touchscreen, and talking with a phone with F1-score 0.84, 0.69, 0.82, respectively. For overall distraction detection, it achieved F1-score of 0.74. The whole framework ran at 28 frames per second. The algorithm achieved comparable overall accuracy with similar research, and was more efficient than other methods. A demo video for the algorithm can be found at https://youtu.be/NKclK1bHRd4.

Visual and Cognitive Demands of CarPlay, Android Auto, and Five Native Infotainment Systems

OBJECTIVE

The present research compared and contrasted the workload associated with using in-vehicle information systems commonly available in five different automotive original equipment manufacturers (OEMs) with that of CarPlay and Android Auto when used in the same vehicles.

BACKGROUND

A growing trend is to provide access to portable smartphone-based systems (e.g., CarPlay and Android Auto) that support an expansion of various in-vehicle infotainment system features and functions.

METHOD/RESULTS

The study involved on-road testing of 24 participants in each configuration of five vehicles crossed with the three different infotainment systems: the embedded portion of the native OEM systems, CarPlay, and Android Auto. Our analysis found that workload was significantly greater for the embedded portion of the native OEM systems than for CarPlay and Android Auto. The strengths and weaknesses of each CarPlay and Android Auto traded off in such a way that the overall demand associated with using the two systems did not differ.

CONCLUSION

CarPlay and Android Auto provided more functionality and resulted in lower levels of workload than the embedded portion of the native OEM infotainment systems.

APPLICATION

Potential applications of this research include refinements to CarPlay and Android Auto to address variations in workload as a function of task type, the modality of interaction, and OEM implementation of the system.

Vehicle and Highway Adaptations to Compensate for Sleepy Drivers

Sleepiness remains a major contributor to road crashes. Driver monitoring systems identify early signs of sleepiness and alert drivers, using real-time analysis of eyelid movements, EEG activity, and steering control. Other vehicle adaptations warn drivers of lane departures or collision hazards, with higher vehicle automation actively taking over vehicle control to prevent run off the road incidents and institute emergency braking. Similarly, road adaptations warn drivers (rumble strips) or mitigate crash severity (barriers). Infrastructure to encourage drivers to use countermeasures, such as rest stops for napping, is also important. The effectiveness of adaptations varies for different road users.

Prediction of drowsiness events in night shift workers during morning driving

The morning commute home is an especially vulnerable time for workers engaged in night shift work due to the heightened risk of experiencing drowsy driving. One strategy to manage this risk is to monitor the driver's state in real time using an in vehicle monitoring system and to alert drivers when they are becoming sleepy. The primary objective of this study is to build and evaluate predictive models for drowsiness events occurring in morning drives using a variety of physiological and performance data gathered under a real driving scenario. We used data collected from 16 night shift workers who drove an instrumented vehicle for approximately two hours on a test track on two occasions: after a night shift and after a night of rest. Drowsiness was defined by two outcome events: performance degradation (Lane-Crossing models) and electroencephalogram (EEG) characterized sleep episodes (Microsleep Models). For each outcome, we assessed the accuracy of sets of predictors, including or not including a driver factor, eyelid measures, and driving performance measures. We also compared the predictions using different time intervals relative to the events (e.g., 1-min prior to the event through 10-min prior). By examining the Area Under the receiver operating characteristic Curve (AUC), accuracy, sensitivity, and specificity of the predictive models, the results showed that the inclusion of an individual driver factor improved AUC and prediction accuracy for both outcomes. Eyelid measures improved the prediction for the Lane-Crossing models, but not for Microsleep models. Prediction performance was not changed by adding driving performance predictors or by increasing the time to the event for either outcome. The best models for both measures of drowsiness were those considering driver individual differences and eyelid measures, suggesting that these indicators should be strongly considered when predicting drowsiness events. The results of this paper can benefit the development of real-time drowsiness detection and help to manage drowsiness to avoid related motor-vehicle crashes and loss.

Consumer Information Potpourri: Instructional and Operational Variability Among Passenger Vehicle Automated Systems

Even owners of the most advanced vehicles often have little understanding of the available in-vehicle technology. Accessible safety-critical information and standard instructional and operational components are potential routes to increase drivers’ knowledge. This article presents a review of information obtained from automobile manufacturers’ websites and operator manuals aimed toward passenger vehicle automated system consumers. This review revealed target areas for researchers, manufacturers, and policy makers to consider. Systems offering comparable functionality varied greatly in their nomenclature, type of feedback provided to drivers, and the accessibility of information about the systems. Also, information pertaining to systems limits was difficult to obtain.

Modelling driver acceptance of driver support systems

Driver support systems are intended to enhance driver performance and improve transportation safety. Even though these systems afford safety advantages, they challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the adoption of new in-vehicle technologies into the transportation system. In this study, a model of driver acceptance of driver support systems was developed. A conceptual driver acceptance model, including several components, was proposed based on a review of current literature. An empirical study was subsequently carried out using an online survey approach. The study collected data on participants' perceptions of two driver support systems (a fatigue monitoring system and an adaptive cruise control system combined with a lane-keeping system) in terms of attitude, perceived usefulness, and other components of driver acceptance. Results identified five components of driver acceptance (attitude, perceived usefulness, endorsement, compatibility, and affordability). The results also confirmed several mediating effects. The developed model was able to explain 85% of the variability in driver acceptance. The model provides an improved understanding how driver acceptance is formed, including which factors affect driver acceptance and how they affect it. The model can also help automakers and researchers to assess the design and estimate the potential use of a driver support system. The model could also be highly beneficial in developing a questionnaire to assess driver acceptance.

Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies

Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems

Advanced Driver Assistance Systems (ADAS) are intended to enhance driver performance and improve transportation safety. The potential benefits of these technologies, such as reduction in number of crashes, enhancing driver comfort or convenience, decreasing environmental impact, etc., have been acknowledged by transportation safety researchers and federal transportation agencies. Although these systems afford safety advantages, they may also challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the implementation of these systems into the transportation system. Recognizing the need for research into the factors affecting driver acceptance, this study assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT) for modelling driver acceptance in terms of Behavioral Intention to use an ADAS. Each of these models propose a set of factors that influence acceptance of a technology. Data collection was done using two approaches: a driving simulator approach and an online survey approach. In both approaches, participants interacted with either a fatigue monitoring system or an adaptive cruise control system combined with a lane-keeping system. Based on their experience, participants responded to several survey questions to indicate their attitude toward using the ADAS and their perception of its usefulness, usability, etc. A sample of 430 surveys were collected for this study. Results found that all the models (TAM, TPB, and UTAUT) can explain driver acceptance with their proposed sets of factors, each explaining 71% or more of the variability in Behavioral Intention. Among the models, TAM was found to perform the best in modelling driver acceptance followed by TPB. The findings of this study confirm that these models can be applied to ADAS technologies and that they provide a basis for understanding driver acceptance.

Age-related differences in fatal intersection crashes in the United States

OBJECTIVE

Given the aging U.S. population and resulting number of older drivers in the coming years, it is important to understand the factors leading to their involvement in vehicle crashes and develop counter-measures to reduce their frequency and severity. This is also useful for helping older adults "age in place" in terms of accessibility, mobility, quality of life and safety. Thus, the objective of this study was to provide up-to-date data on differences in age-related risks and rates for involvement in fatal intersection motor-vehicle crashes in the US.

METHODS

Pooled data for the years 2011-2014 from the FARS, a census of fatal traffic crashes within the 50 States, the District of Columbia, and Puerto Rico, created by the US National Highway Traffic Safety Administration (NHTSA) were used to calculate summary statistics including annualized crash rates. Multivariate logistic regression models were used to evaluate age and gender-related differences in fatal intersection crash risk, controlling for covariates. An induced exposure analysis was conducted to calculate crash involvement ratios (CIRs) for all two-vehicle fatal intersection crashes. Older and younger drivers were compared with respect to the presence of factors related to intersection crashes using a multivariate Poisson regression model.

RESULTS

During the period of 2011-2014, among the reported 120,809 fatal accidents in the US involving 178,489 drivers of vehicles, 48,733 (28%) were drivers involved in fatal intersection crashes. Age-adjusted annualized fatal intersection crash rates per 100,000 licensed drivers were highest for drivers aged 85 or older (9.89/100,000), followed by 20 years of age (8.93/100,000). Teen and older drivers (55+ years of age) were over-involved in fatal intersection crashes, drivers from 20 to 54 years old were under-involved. Male and female drivers, 70-74 years of age, were 20% and 21%, respectively, more likely to be involved in a fatal intersection crash than 20-24year olds (of same gender). By age 85, fatal intersection crash risk for all drivers was almost doubled. Significant differences in factors related to crashes involving younger (<65) and older (65+ years) drivers were time of day, lighting and weather conditions, day of week, roadway type and number of lanes, presence of visible traffic controls, speed limit and estimated driving speed, and whether the driver was deemed at fault for the crash CONCLUSION: The results provide the most up-to-date analysis of aging and fatal intersection crash risk in the US, and underscore several trends worthy of further investigation. Older adults face a number of challenges associated with natural aging, including sensory, perceptual, cognitive and motor declines that may impact their driving. As with younger drivers, expanded or renewed approaches to driver training at licensing renewals, as well as safety-based technological advances are viable avenues toward improving the safety outlook for older adults.

Distraction and task engagement: How interesting and boring information impact driving performance and subjective and physiological responses

As more devices and services are integrated into vehicles, drivers face new opportunities to perform additional tasks while driving. While many studies have explored the detrimental effects of varying task demands on driving performance, there has been little attention devoted to tasks that vary in terms of personal interest or investment-a quality we liken to the concept of task engagement. The purpose of this study was to explore the impact of task engagement on driving performance, subjective appraisals of performance and workload, and various physiological measurements. In this study, 31 participants (M = 37 yrs) completed three driving conditions in a driving simulator: listening to boring auditory material; listening to interesting material; and driving with no auditory material. Drivers were simultaneously monitored using near-infrared spectroscopy, heart monitoring and eye tracking systems. Drivers exhibited less variability in lane keeping and headway maintenance for both auditory conditions; however, response times to critical braking events were longer in the interesting audio condition. Drivers also perceived the interesting material to be less demanding and less complex, although the material was objectively matched for difficulty. Drivers showed a reduced concentration of cerebral oxygenated hemoglobin when listening to interesting material, compared to baseline and boring conditions, yet they exhibited superior recognition for this material. The practical implications, from a safety standpoint, are discussed.

Focal and Ambient Visual Contributions and Driver Visual Scanning in Lane Keeping and Hazard Detection

In some previous simulator studies, we showed that drivers, engaged in a secondary in-vehicle task at different display separations, were able to buffer some aspects of the driving task (e.g., vehicle control), but not others (e.g., hazard response; Horrey & Wickens, 2002, Horrey, Alexander, & Wickens, 2003). We speculate that this pattern of results may be a result of effective time-sharing between the ambient visual task of vehicle control and the focal visual in-vehicle task, but task interference between the in-vehicle task and the focal task of hazard detection and identification. Alternatively, drivers may be using an optimal scanning strategy that allows them to effectively monitor both the roadway and the in-vehicle device. In this paper, we detail some of the theoretical background, describe some relevant research, and present a model of scanning behavior.

The Effects of Head-Up Display Clutter and In-Vehicle Display Separation on Concurrent Driving Performance

The introduction of new in-vehicle technologies (IVTs) in automobiles may have important implications for driver safety, especially to the extent that these devices interfere with the primary driving task. Two experiments explored the effects of IVTs on vehicle control and hazard awareness: specifically, we were interested in the impact of visual clutter from head-up display (HUD) overlay as well as the impact of display separation. In experiment 1, twenty-five drivers in a wrap-around simulator drove urban and rural routes while performing a phone number read-back task. Visual displays were located either in a HUD overlaid on the horizon, a HUD positioned 7° below the horizon, or on a head-down display (HDD) located near the mid-console. Experiment 2 attempted to replicate some of the key findings in Experiment 1 with more challenging driving conditions (i.e., curved roads, varying fog densities). In general, the results suggested that drivers protected the vehicle control task, however there were costs in hazard response time and side task performance with the HDD. We suggest that effective hazard detection requires more focal visual resources whereas vehicle control may utilize ambient resources. The practical and theoretical significance of these findings are discussed.

A Computational Model of Attention/Situation Awareness

A computational model of attention and situation awareness (SA) was developed and used to predict pilot errors in the task of taxiing from runway to terminal. The model incorporates a low-level perception/attention module and a higher-level belief-updating module. Attentional scanning is controlled by bottom-up and top-down processes, with the effectiveness of top-down guidance varying as a function of SA. Information sampled by the low-level module is fed forward to the higher-level module for consolidation within a working memory representation of the pilot's situation, with the quality of this representation reflecting the pilot's level of SA. The model was validated by comparing its predictions to the behavior of pilots performing a taxiway simulation. Results indicate that the model successfully predicts the improved performance associated with display augmentations, and provides construct validity regarding the effects of visibility, distraction, and degraded information quality.

Supporting Situation Assessment Through Attention Guidance: A Cost-Benefit and Depth of Processing Analysis

Automated support systems may be useful tools for aiding situation assessment in complex environments such as the military battlefield. These environments are marked by large amounts of information which often must be weighted and integrated into a meaningful judgment or assessment. The present research examines the effects of attention cueing on information integration tasks in static battlefield situations. Sixteen participants completed a resource allocation task for 56 battlefield scenarios (based on perceived threats). For half the trials, an automated system guided their attention to high-threat units. On 2 trials a memory probe was administered to assess the depth of processing of information, and on the final trial an automation failure was presented. Results demonstrated an overall allocation performance advantage for automation but poorer recall for automation-enhanced units. Half of the participants failed to attend to the system failure. Those participants who detected the failure were inferred to have processed the cues more deeply on the memory trials. The costs and benefits of automated cueing are discussed.

Assessing Interference from Mental Workload Using a Naturalistic Simulated Driving Task: A Pilot Study

Previous work has shown that drivers engaged in concurrent cognitive tasks exhibit some adaptive behaviors to enhance safety, such as increasing their headway distance, despite the fact that other aspects of safety might be compromised. However, these studies often test steady-state behaviors (e.g., car-following) that might not be representative of traffic situations in which drivers' goals and intentions are constantly changing (i.e., involving tactical vehicle control). In two simulator experiments, we examined the impact of mental workload on drivers engaged in a “naturalistic” tactical driving task. In Experiment 1, we explored the safety margins (distances) that drivers maintain between themselves and vehicles around them when completing a passing maneuver. In Experiment 2, we examined safety margins and performance under less constrained, yet more realistic and dynamic conditions. In both experiments, we found no evidence that drivers adjust their safety margins to account for the additional demands of performing a cognitive task. The implications for steady-state experimental scenarios versus more dynamic ones are discussed.

Age-Related Differences in Vehicle Control and Eye Movement Patterns at Intersections: Older and Middle-Aged Drivers

Older drivers are at increased risk of intersection crashes. Previous work found that older drivers execute less frequent glances for detecting potential threats at intersections than middle-aged drivers. Yet, earlier work has also shown that an active training program doubled the frequency of these glances among older drivers, suggesting that these effects are not necessarily due to age-related functional declines. In light of findings, the current study sought to explore the ability of older drivers to coordinate their head and eye movements while simultaneously steering the vehicle as well as their glance behavior at intersections. In a driving simulator, older (M = 76 yrs) and middle-aged (M = 58 yrs) drivers completed different driving tasks: (1) travelling straight on a highway while scanning for peripheral information (a visual search task) and (2) navigating intersections with areas potential hazard. The results replicate that the older drivers did not execute glances for potential threats to the sides when turning at intersections as frequently as the middle-aged drivers. Furthermore, the results demonstrate costs of performing two concurrent tasks, highway driving and visual search task on the side displays: the older drivers performed more poorly on the visual search task and needed to correct their steering positions more compared to the middle-aged counterparts. The findings are consistent with the predictions and discussed in terms of a decoupling hypothesis, providing an account for the effects of the active training program.

The effects of brief visual interruption tasks on drivers' ability to resume their visual search for a pre-cued hazard

Driver visual distraction is known to increase the likelihood of being involved in a crash, especially for long glances inside the vehicle. The detrimental impact of these in-vehicle glances may carry over and disrupt the ongoing processing of information after the driver glances back up on the road. This study explored the effect of different types of visual tasks inside the vehicle on the top-down processes that guide the detection and monitoring of road hazards after the driver glances back towards the road. Using a driving simulator, 56 participants were monitored with an eye tracking system while they navigated various hazardous scenarios in one of four experimental conditions. In all conditions, a potential hazard was visible 4-5s before the driver could strike the potential hazard were it to materialize. All interruptions were exactly two seconds in length. After the interruption the potential hazard again became visible for about a half-second after which the driver passed by the hazard. The nature of the in-vehicle visual interruption presented to the participants was varied across conditions: (1) Visual interruptions comprised of spatial, driving unrelated, tasks; (2) visual interruptions comprised of non-spatial, driving unrelated, tasks; (3) visual interruptions with no tasks added; and (4) no visual interruptions. In the first three conditions drivers glancing on the forward roadway was momentarily interrupted (either with or without a task) just after the potential hazard first became visible by the occurrence of an in-vehicle task lasting two seconds. In the last condition (no interruptions) the driver could not see the potential hazard after it just became visible because of obstructions in the built or natural environment. The obstruction (like the interruption) lasted for two seconds. In other words, across all conditions the hazard was visible, then became invisible, and finally became visible again. Importantly, the results show that the presence of an interruption (as opposed to an obstruction) negatively impacted drivers' ability to anticipate the potential hazard. Moreover, the various types of interruptions had differential effects on hazard detection. The implications of this study for the design of in-vehicle displays are discussed.

Measurement of driver calibration and the impact of feedback on drivers' estimates of performance

Recent studies focused on driver calibration show that drivers are often miscalibrated, either over confident or under confident, and the magnitude of this miscalibration changes under different conditions. Previous work has demonstrated behavioral and performance benefits of feedback, yet these studies have not explicitly examined the issue of calibration. The objective of this study was to examine driver calibration, i.e., the degree to which drivers are accurately aware of their performance, and determine whether feedback alters driver calibration. Twenty-four drivers completed a series of driving tasks (pace clocks, traffic light, speed maintenance, and traffic cones) on a test track. Drivers drove three different blocks around the test track: (1) baseline block, where no participants received feedback; (2) feedback block, where half of the participants received performance feedback while the other half received no feedback; (3) a no feedback block, where no participants received feedback. Results indicated that across two different calibration measures, drivers were sufficiently calibrated to the pace clocks, traffic light, and traffic cone tasks. Drivers were not accurately aware of their performance regarding speed maintenance, though receiving feedback on this task improved calibration. Proper and accurate measurements of driver calibration are needed before designing performance feedback to improve calibration as these feedback systems may not always yield the intended results.

High risk of near-crash driving events following night-shift work

Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual night-shift work on measures of drowsiness and driving performance while operating a real motor vehicle remains unknown. Sixteen night-shift workers completed two 2-h daytime driving sessions on a closed driving track at the Liberty Mutual Research Institute for Safety: (i) a postsleep baseline driving session after an average of 7.6 ± 2.4 h sleep the previous night with no night-shift work, and (ii) a postnight-shift driving session following night-shift work. Physiological measures of drowsiness were collected, including infrared reflectance oculography, electroencephalography, and electrooculography. Driving performance measures included lane excursions, near-crash events, and drives terminated because of failure to maintain control of the vehicle. Eleven near-crashes occurred in 6 of 16 postnight-shift drives (37.5%), and 7 of 16 postnight-shift drives (43.8%) were terminated early for safety reasons, compared with zero near-crashes or early drive terminations during 16 postsleep drives (Fishers exact: P = 0.0088 and P = 0.0034, respectively). Participants had a significantly higher rate of lane excursions, average Johns Drowsiness Scale, blink duration, and number of slow eye movements during postnight-shift drives compared with postsleep drives (3.09/min vs. 1.49/min; 1.71 vs. 0.97; 125 ms vs. 100 ms; 35.8 vs. 19.1; respectively, P < 0.05 for all). Night-shift work increases driver drowsiness, degrading driving performance and increasing the risk of near-crash drive events. With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety.

Sequential in-vehicle glance distributions: an alternative approach for analyzing glance data

OBJECTIVE

The aim of this study was to illustrate how a consideration of glance sequences to in-vehicle tasks and their associated distributions can be informative.

BACKGROUND

The rapid growth in the number of nomadic technologies and in-vehicle devices has the potential to create complex, visually intensive tasks for drivers that may incur long in-vehicle glances. Such glances place drivers at increased risk of a motor vehicle crash.

METHOD

We used eye-glance data from a study of distraction training programs to examine the change in glance duration distributions across consecutive glances during the performance of various in-vehicle tasks.

RESULTS

The sequential analysis across trained and untrained drivers showed that the proportion of late-sequence glances longer than a 2-s threshold among untrained drivers was almost double the number of such glances for the trained drivers, that the third and later glances were particularly problematic, and that training reduced the proportion of early- and later-sequence glances.

CONCLUSION

Examining how the duration of off-road glances varies as a function of their order in a sequence of glances and the visual demands of the task can offer important insights into the change in the distracting potential of in-vehicle tasks across glances and the effects of training.

APPLICATION

The sequential analysis of in-vehicle glance data can be useful for researchers and practitioners and has implications for the development and evaluation of training programs as well as for task and interface design.

Calibration of skill and judgment in driving: development of a conceptual framework and the implications for road safety

Humans often make inflated or erroneous estimates of their own ability or performance. Such errors in calibration can be due to incomplete processing, neglect of available information or due to improper weighing or integration of the information and can impact our decision-making, risk tolerance, and behaviors. In the driving context, these outcomes can have important implications for safety. The current paper discusses the notion of calibration in the context of self-appraisals and self-competence as well as in models of self-regulation in driving. We further develop a conceptual framework for calibration in the driving context borrowing from earlier models of momentary demand regulation, information processing, and lens models for information selection and utilization. Finally, using the model we describe the implications for calibration (or, more specifically, errors in calibration) for our understanding of driver distraction, in-vehicle automation and autonomous vehicles, and the training of novice and inexperienced drivers.

Reading text while driving: understanding drivers' strategic and tactical adaptation to distraction

OBJECTIVE

In this study, we investigated how drivers adapt secondary-task initiation and time-sharing behavior when faced with fluctuating driving demands.

BACKGROUND

Reading text while driving is particularly detrimental; however, in real-world driving, drivers actively decide when to perform the task.

METHOD

In a test track experiment, participants were free to decide when to read messages while driving along a straight road consisting of an area with increased driving demands (demand zone) followed by an area with low demands. A message was made available shortly before the vehicle entered the demand zone. We manipulated the type of driving demands (baseline, narrow lane, pace clock, combined), message format (no message, paragraph, parsed), and the distance from the demand zone when the message was available (near, far).

RESULTS

In all conditions, drivers started reading messages (drivers' first glance to the display) before entering or before leaving the demand zone but tended to wait longer when faced with increased driving demands. While reading messages, drivers looked more or less off road, depending on types of driving demands.

CONCLUSIONS

For task initiation, drivers avoid transitions from low to high demands; however, they are not discouraged when driving demands are already elevated. Drivers adjust time-sharing behavior according to driving demands while performing secondary tasks. Nonetheless, such adjustment may be less effective when total demands are high.

APPLICATION

This study helps us to understand a driver's role as an active controller in the context of distracted driving and provides insights for developing distraction interventions.

Memory for a Hazard is Interrupted by Performance of a Secondary In-Vehicle Task

Driver visual distraction is known to increase the likelihood of being involved in a crash, especially for long glances. Recent evidence further suggests that the detrimental impact of these glances carries over and disrupting the ongoing processing of information after the eyes return to the road. This study aimed at exploring the effect of different types of visual disruptions on the top-down processes that guide the detection and monitoring of road hazards. Using a driving simulator, 56 participants were monitored with an eye tracking system while they navigated various hazardous scenarios in one of four experimental conditions: (1) Visual interruptions comprised of spatial, driving unrelated, tasks; (2) visual interruptions comprised of non-spatial, driving unrelated, tasks; (3) visual interruptions with no tasks added; and (4) no visual interruptions. In the first three conditions drivers were momentarily interrupted (either with or without a task) prior to the hazard occurrence. The visual interruption was aimed to simulate a glance inside the vehicle either with or without the need to process driving irrelevant information. Results show that the various types of tasks had differential effects on hazard detection. Implications of this study are discussed.

A Looming Crisis

Long glances away from the road present a significant risk to driving safety. The tail of the distribution for in-vehicle glance duration has been proposed to be more relevant to crash risk than the mean of the distribution. Using data collected in the 100-Car Naturalistic Driving Study (Dingus et al., 2006), this study examined the changes in the distribution of driver off-road glance duration, as well as in the frequency of such glances, at different time points before crash/near-crash events and compared with baseline (i.e., normal) driving. The results showed that the shape of the distribution of off-road glance duration at the onset of the precipitating factor of crashes/near-crashes was similar to the distribution in epochs during the preceding 25 seconds; nonetheless, the frequency of off-road glances increased in the approach to crashes/near-crash events. Compared with baseline epochs, drivers in crashes/near-crash events tended to look away from the forward road more often and with longer duration (i.e., with thicker tail end of the distributions; exceeding 1.7 seconds as observed in the distributions). It suggests that frequent off-road glances longer than 1.7 seconds present a high-risk glance pattern in the seconds preceding a safety- critical event and that the 2.0 second-threshold that is frequently cited in defining dangerously long off-road glances might be a liberal estimation.

The effects of momentary visual disruption on hazard anticipation and awareness in driving

OBJECTIVE

Driver distraction is known to increase crash risk, especially when a driver glances inside the vehicle for especially long periods of time. Though it is clear that such glances increase the risk for the driver when looking inside the vehicle, it is less clear how these glances disrupt the ongoing processing of information outside the vehicle once the driver's eyes return to the road. The present study was aimed at exploring the effect of in-vehicle glances on the top-down processes that guide the detection and monitoring of hazards on the forward roadway.

METHOD

Using a driving simulator, 12 participants were monitored with an eye-tracking system while they navigated various hazardous scenarios. Six participants were momentarily interrupted by a visual secondary task (simulating a glance inside the vehicle) prior to the occurrence of a potential hazard and 6 were not.

RESULTS

Eye movement analyses showed that interrupted drivers often failed to continue scanning for a potential hazard when their forward view reappeared, especially when the potential threat could not easily be localized. Additionally, drivers' self-appraisal of workload and performance of the driving task indicated that, contrary to what one might expect, drivers in the interruption condition reported workload levels lower than and performance equal to drivers in the no interruption condition.

CONCLUSIONS

Drivers who are momentarily disrupted even for a brief duration are at risk of missing important information when they return their gaze to the forward roadway. In addition, because they are not aware of missing this information they are likely to continue engaging in in-vehicle tasks even though they are demonstrably unsafe. The implications for safety, calibration, and targeted remediation are discussed.

The use of contextual cues to improve warning symbol comprehension: making the connection for older adults

This study teased apart the effects of comprehensibility and complexity on older adults' comprehension of warning symbols by manipulating the relevance of additional information in further refining the meaning of the symbol. Symbols were systematically altered such that increased visual complexity (in the form of contextual cues) resulted in increased comprehensibility. One hundred older adults, aged 50-71 years, were tested on their comprehension of these symbols before and after training. High comprehensibility-complexity symbols were found to be better understood than low- or medium-comprehensibility-complexity symbols and the effectiveness of the contextual cues varied as a function of training. Therefore, the nature of additional detail determines whether increased complexity is detrimental or beneficial to older adults' comprehension - if the additional details provide 'cues to knowledge', older adults' comprehension improves as a result of the increased complexity. However, some cues may require training in order to be effective.

PRACTITIONER SUMMARY

Research suggests that older adults have greater difficulty in understanding more complex symbols. However, we found that when the complexity of symbols was increased through the addition of contextual cues, older adults' comprehension actually improved. Contextual cues aid older adults in making the connection between the symbol and its referent.

Reading While Driving: A Study on Drivers’ Strategies of In-Vehicle Task Initiation

In spite of increased public awareness and an ever-growing body of research, driver distraction remains an important safety concern. Reading text while driving may be especially detrimental by imposing both visual interference and extra cognitive demand on drivers. However, in most cases, drivers do not passively respond to such a task, they actively decide when to perform the task. The current study investigated drivers’ strategies with respect to the initiation of text reading when faced with fluctuations in driving demand. Text messages were made available to participants shortly before the vehicle entered an area with increased driving demands ( demand zone). Participants were asked to read the message before the end of the trial, but were free to decide when and how to read the messages. We manipulated the type of driving demand (baseline; three levels of high demand—narrow lane, pace clock, and ultimate [narrow + pace clock]), format of text (no message; paragraph; parsed), and the distance from start of message to the demand zone (near; far). The results showed that in most cases drivers started to read the text message before or in the demand zone even though they would have enough time to complete the task after passing the area. Nonetheless, task initiation time (measured from the appearance of the message to the drivers’ first glance to the display) increased when driving was demanding compared to the baseline condition. It suggests that drivers may be sensitive to transitions from low to high demand when initiating secondary tasks, however are not discouraged from such activities when demands are already elevated.

On-board safety monitoring systems for driving: review, knowledge gaps, and framework

INTRODUCTION

Fatal highway incidents remain the leading type of fatal work-related event, carrying tremendous personal, social, and economic costs. While employers with a fixed worksite can observe and interact directly with workers in an effort to promote safety and reduce risk, employers with workers who operate a motor vehicle as part of their job have fewer options. New technologies such as on-board safety monitoring systems offer the potential to further improve safety. These technologies allow vehicle owners to collect safety-specific information related to a driver's on-the-road behavior and performance. While many such devices are being developed and implemented in both commercial fleets and private vehicles, the scientific examination of these devices has lagged by comparison.

METHOD

In the current paper, we: (a) describe the general features and functionality of current generations of on-board monitoring devices and how they might impact various driver behaviors; (b) review the current state of scientific knowledge specific to on-board devices; (c) discuss knowledge gaps and potential areas for future research, borrowing from the related domain of computer-based electronic performance monitoring (EPM); and (d) propose a framework that can be used to explore some of the human-system interactions pertaining to monitoring systems.

IMPACT ON INDUSTRY

Motor vehicle crashes can carry tremendous costs for employers, in terms of injury, disability, and loss of potentially productive work years. New technologies can offer tremendous benefits in terms of promoting safer on-the-road behaviors.

Assessing the Effects of In-Vehicle Tasks on Driving Performance

New technologies and devices inside the automobile can compete for drivers’ limited attention, raising concerns about driver distraction. This article provides a short overview of some of the issues surrounding in-vehicle tasks, particularly their impact on visual scanning and driving performance. Evidence from a variety of experimental approaches offers key scientific findings that form the basis for taking action to prevent and manage distraction – through the design of products, advanced technology, legislation, and education and training applications.

Age-related differences in warning symbol comprehension and training effectiveness: effects of familiarity, complexity, and comprehensibility

Age-related changes in selective attention, inhibitory efficiency, and the ability to form new associations suggest that older adults may have greater difficulty with more complex and less comprehensible symbols. We examined comprehension of symbols varying in terms of ratings of familiarity, complexity, and comprehensibility, by younger (aged 18-35) and older (aged 55-70) adults. It was found that older adults have greater difficulty than younger adults in comprehending warning symbols and that accident scenario training improves comprehension. Regression analyses indicated that familiarity and comprehensibility were important in determining performance on the pre-training comprehension test by both younger and older adults. However, training eliminated the effects of stimulus characteristics for younger adults, while older adults' comprehension continued to be significantly influenced by comprehensibility. We suggest that symbol design incorporates cues to knowledge to facilitate the linkage between new knowledge (i.e. the warning symbol) and relevant knowledge in long-term memory. Statement of Relevance: Symbol characteristics play an important role in age-related differences in warning symbol comprehension. To optimise comprehension by older adults, symbols should have a clear relationship with areal-world referent. Alternatively, symbol design could incorporate cues to knowledge to facilitate the linkage between new knowledge and relevant knowledge in long-term memory.

Future directions in fatigue and safety research

Fatigue is regarded as a major contributor to workplace and highway morbidity and mortality. While the scientific literature is replete with studies that can be traced back more than a hundred years, much remains to be done to improve our knowledge of and ability to alleviate the consequences of fatigue. Moreover, given the dramatic transformation of modern work systems due to a global and 24/7 economy, there is increasing urgency in improving our understanding of fatigue as a safety risk factor, its etiology and management. As a result, a Hopkinton Conference was organized to review the state of knowledge in the area and define future directions for research aimed at preventing or mitigating the consequences of fatigue. The Hopkinton Conference paradigm brings together leading experts on a key research area to define scientific gaps and research needs, and serves as a stimulus for further collaboration. Over the course of several months prior to the conference, participants draft state-of-the-art reviews covering various aspects of the research topic. In this case, five working groups were formed, each charged with developing collaborative manuscripts in a given topic area of interest, as follows: the Link Between Fatigue and Safety, Demographic Issues in Fatigue, Predicting Fatigue, Technological Approaches in the Management of Fatigue, and Organizational Factors in the Management of Fatigue. The participants then convened for a 2 day conference at the Liberty Mutual Research Institute for Safety in Hopkinton to review, debate, and revise the draft manuscripts; examine global issues; and discuss research priorities. The output from this collective effort is captured in this special issue of Accident Analysis and Prevention.

The challenges and opportunities of technological approaches to fatigue management

There are a number of different strategies to mitigate the effects of fatigue in transportation and other occupational settings. Many are centered on regulatory or organizational approaches, such as work scheduling restriction and employer screening practices. While these generally benefit safety and productivity, there are clearly limitations to these approaches. Technologies that objectively detect or predict operator fatigue may be used to effectively complement or even supplant organizational or regulatory approaches. Over the past decade and a half, there have been considerable advances in relevant technologies, including onboard devices that monitor drivers' state or level of performance as well as devices that predict fatigue in advance of a work cycle or trip. In this paper, we discuss the challenges and opportunities for technological approaches to fatigue management, beginning with a discussion of the "ideal" system, followed by some of the general issues and limitations of current technologies. We also discuss some of the critical and outstanding issues related to the human interaction with these systems, including user acceptance and compliance. Finally, we discuss future directions in next generation technology for fatigue management.

Research needs and opportunities for reducing the adverse safety consequences of fatigue

Although there has been a significant amount of research on fatigue globally, it remains a major contributor to workplace and highway mortality and morbidity. Given its importance, a Hopkinton Conference was organized to review and discuss the state of knowledge in the area and to define future directions for research aimed at preventing or mitigating the consequences of fatigue. In all, five groups of international contributors produced six articles for this special issue, comprising state of the art reviews, along with a discussion of knowledge gaps and future research needs. In this concluding paper, we capture some of the major outcomes and recommendations from this process. These are organized into five topic areas: the link between fatigue and safety, demographic issues in fatigue, modeling and predicting fatigue, technological approaches to fatigue management, and organizational factors in fatigue management.

The effect of feedback on attitudes toward cellular phone use while driving: a comparison between novice and experienced drivers

OBJECTIVES

To assess and compare the effectiveness of a simulation-based approach to change drivers' attitudes toward cellular phone use while driving for younger novice and older experienced drivers.

METHODS

Thirty young novice drivers were tested on a driving simulator in this study. Their performance in dealing with driving tasks was measured for a single task and dual tasks (driving while using a cellular phone) and compared to 30 older experienced drivers tested previously in another study. Half of the younger drivers received video-based feedback regarding their performance in the two conditions, with an emphasis on the contribution of dual-tasking to degraded performance. The other half did not receive any performance feedback. Drivers' perceptions and attitudes toward cellular phone use while driving were investigated by a questionnaire before, immediately after, and again one month following the simulation-based testing for both groups of drivers (feedback; no feedback).

RESULTS

All drivers (including the novice and experienced) reported willingness to engage in driving and talking on a cellular phone in some situations. The simulated driving test showed that a secondary cellular phone task significantly degraded driving performance for both the novice and the experienced drivers. The feedback treatment group (both the novice and the experienced) showed significant attitude change toward cellular phone use while driving (toward being less favorable), whereas the control group had no attitude change. At the one-month follow-up, the benefit of feedback was sustained more so in the experienced driver group than the novice driver group, although both groups still benefited relative to the control conditions.

CONCLUSIONS

Simulation-based feedback training is promising for short-term education in novice drivers but may be more effective in the long-term for drivers with higher levels of experience. Drivers with more experience appear to have a greater, more sustained benefit from the training than novices. Additional research is needed to better tailor this education method toward novice drivers.

IMPACT

Simulation-based participative education approach through feedback needs to be better tailored toward novice drivers.

Effects of a computer-based training module on drivers' willingness to engage in distracting activities

OBJECTIVE

This study examines the effect of a computer-based training module on drivers' attitudes and behaviors with respect to in-vehicle distraction.

BACKGROUND

Research findings on the negative performance implications of distraction call for the need to mitigate these adverse effects.

METHOD

Forty drivers (ages 18 to 20 yrs) were divided into two groups: a training group that completed the module and a control group that viewed an unrelated video. The training promoted enhanced metacognitive skills (e.g., planning, monitoring) and strategies to deal with distraction. Measures of willingness to perform in-vehicle activities while driving (involving the use of short videos) were assessed before and after the intervention. Drivers also performed in-vehicle tasks while driving an instrumented vehicle on a closed test track.

RESULTS

Following the training, drivers in the training group showed a decline in their ratings of willingness to engage in distracting activities along with a corresponding increase in perceived risk. In contrast, ratings from drivers in the control group did not change on any measures. Drivers in the training group were also more likely to perform in-vehicle tasks while the vehicle was parked compared with the control group-an obvious safety benefit. However, there was no observable benefit of training for drivers who performed the distracting tasks while the vehicle was in motion.

CONCLUSION

There may be some promise to such a training approach. The implications for distraction and training are discussed.

APPLICATION

Training general skills in dealing with potentially distracting in-vehicle tasks may help offset some of the negative outcomes associated with their use.

The effect of conformity tendency on pedestrians' road-crossing intentions in China: an application of the theory of planned behavior

This paper presents a survey investigating the effects of age, gender and conformity tendency on Chinese pedestrians' intention to cross the road in potentially dangerous situations. A sample of 426 respondents completed a demographic questionnaire, a scale measuring their tendency towards social conformity, and a questionnaire based on the theory of planned behavior (TPB). This questionnaire measured people's intentions to cross the road in two different road crossing situations, their attitude towards the behavior, subjective norms, perceived behavioral control, anticipated affect, moral norms, and perceived risk. The two scenarios depicted (i) a situation where the crossing was consistent with other pedestrians' behavior (Conformity scenario) and (ii) a situation where the road crossing was inconsistent with other pedestrians (Non-Conformity scenario). Pedestrians reported greater likelihood in crossing the road when other pedestrians were crossing the road. People who showed greater tendencies towards social conformity also had stronger road crossing intentions than low conformity people for both scenarios. The predictive model explained 36% and 48% of the variance in the Non-Conformity and Conformity scenarios, respectively. Attitude, subjective norm, perceived behavioral control, and perceived risk emerged as the common predictors for both situations. The results have a number of theoretical and practical implications. In particular, interventions should focus on perceptions of risk that inform road users that crossing with other pedestrians against the signal is also unsafe and prohibited, and may lead to negative outcomes.