Alcohol impairs driver attention and prevents compensatory strategies.

While the negative effects of alcohol on driving performance are undisputed, it is unclear how driver attention, eye movements and visual information sampling are affected by alcohol consumption. A simulator study with 35 participants was conducted to investigate whether and how a driver's level of attention is related to self-paced non-driving related task (NDRT)-engagement and tactical aspects of undesirable driver behaviour under increasing levels of breath alcohol concentration (BrAC) up to 1.0 ‰. Increasing BrAC levels lead to more frequent speeding, short time headways and weaving, and higher NDRT engagement. Instantaneous distraction events become more frequent, with more and longer glances to the NDRT, and a general decline in visual attention to the forward roadway. With alcohol, the compensatory behaviour that is typically seen when drivers engage in NDRTs did not appear. These findings support the theory that alcohol reduces the ability to shift attention between multiple tasks. To conclude, the independent reduction in safety margins in combination with impaired attention and an increased willingness to engage in NDRTs is likely the reason behind increased crash risk when driving under the influence of alcohol.

A Review of Occlusion as a Tool to Assess Attentional Demand in Driving.

OBJECTIVE: The aim of this review is to identify how visual occlusion contributes to our understanding of attentional demand and spare visual capacity in driving and the strengths and limitations of the method. BACKGROUND: The occlusion technique was developed by John W. Senders to evaluate the attentional demand of driving. Despite its utility, it has been used infrequently in driver attention/inattention research. METHOD: Visual occlusion studies in driving published between 1967 and 2020 were reviewed. The focus was on original studies in which the forward visual field was intermittently occluded while the participant was driving. RESULTS: Occlusion studies have shown that attentional demand varies across situations and drivers and have indicated environmental, situational, and inter-individual factors behind the variability. The occlusion technique complements eye tracking in being able to indicate the temporal requirements for and redundancy in visual information sampling. The proper selection of occlusion settings depends on the target of the research. CONCLUSION: Although there are a number of occlusion studies looking at various aspects of attentional demand, we are still only beginning to understand how these demands vary, interact, and covary in naturalistic driving. APPLICATION: The findings of this review have methodological and theoretical implications for human factors research and for the development of distraction monitoring and in-vehicle system testing. Distraction detection algorithms and testing guidelines should consider the variability in drivers' situational and individual spare visual capacity.

Eye Tracking in Driver Attention Research-How Gaze Data Interpretations Influence What We Learn.

Eye tracking (ET) has been used extensively in driver attention research. Amongst other findings, ET data have increased our knowledge about what drivers look at in different traffic environments and how they distribute their glances when interacting with non-driving related tasks. Eye tracking is also the go-to method when determining driver distraction via glance target classification. At the same time, eye trackers are limited in the sense that they can only objectively measure the gaze direction. To learn more about why drivers look where they do, what information they acquire foveally and peripherally, how the road environment and traffic situation affect their behavior, and how their own expertise influences their actions, it is necessary to go beyond counting the targets that the driver foveates. In this perspective paper, we suggest a glance analysis approach that classifies glances based on their purpose. The main idea is to consider not only the intention behind each glance, but to also account for what is relevant in the surrounding scene, regardless of whether the driver has looked there or not. In essence, the old approaches, unaware as they are of the larger context or motivation behind eye movements, have taken us as far as they can. We propose this more integrative approach to gain a better understanding of the complexity of drivers' informational needs and how they satisfy them in the moment.

Truck drivers' interaction with cyclists in right-turn situations.

One of the more hazardous situations for a bicyclist is to go straight on in an intersection where a motor vehicle is turning right, and especially so when heavy vehicles are involved. The aim of this study was to investigate truck drivers' speed choice, gaze behaviour and interaction strategies in relation to vulnerable road users (VRU) when turning right in signalised and non-signalised intersections. Truck drivers experienced (n = 14) or inexperienced (n = 15) with urban traffic drove a 15 km long test route in an urban environment. To guarantee the presence of VRUs, a confederate cyclist with the task to cycle straight on was present in three intersections. Overall, the results suggest that the specific experience of driving a truck in the city has little effect on the strategies employed when interacting with cyclists in a right turn scenario. Neither gaze nor strategic placement or speed related variables differed significantly between the groups, though the drivers inexperienced with urban traffic tended to be more cautious. Glance and driving behaviour were more related to the preconditions afforded by the infrastructure and to interaction type, which is a combination of those infrastructural preconditions and the truck driver's own choice of action. The likelihood of a favourable interaction should be increased, where the truck remains behind the VRUs on the approach to the intersection, something which eliminates the potential for a collision. Education of truck drivers, infrastructure design and improved traffic light sequences are potential ways to reduce the occurrence of more demanding and dangerous interaction types.

Attentional Demand as a Function of Contextual Factors in Different Traffic Scenarios.

OBJECTIVE: To assess the attentional demand of different contextual factors in driving. BACKGROUND: The attentional demand on the driver varies with the situation. One approach for estimating the attentional demand, via spare capacity, is to use visual occlusion. METHOD: Using a 3 × 5 within-subjects design, 33 participants drove in a fixed-base simulator in three scenarios (i.e., urban, rural, and motorway), combined with five fixed occlusion durations (1.0, 1.4, 1.8, 2.2, and 2.6 s). By pressing a microswitch on a finger, the driver initiated each occlusion, which lasted for the same predetermined duration within each trial. Drivers were instructed to occlude their vision as often as possible while still driving safely. RESULTS: Stepwise logistic regression per scenario indicated that the occlusion predictors varied with scenario. In the urban environment, infrastructure-related variables had the biggest influence, whereas the distance to oncoming traffic played a major role on the rural road. On the motorway, occlusion duration and time since the last occlusion were the main determinants. CONCLUSION: Spare capacity is dependent on the scenario, selected speed, and individual factors. This is important for developing workload managers, infrastructural design, and aspects related to transfer of control in automated driving. APPLICATION: Better knowledge of the determinants of spare capacity in the road environment can help improve workload managers, thereby contributing to more efficient and safer interaction with additional tasks.

On the Difference Between Necessary and Unnecessary Glances Away From the Forward Roadway: An Occlusion Study on the Motorway.

OBJECTIVE: The present study strove to distinguish traffic-related glances away from the forward roadway from non-traffic-related glances while assessing the minimum amount of visual information intake necessary for safe driving in particular scenarios. BACKGROUND: Published gaze-based distraction detection algorithms and guidelines for distraction prevention essentially measure the time spent looking away from the forward roadway, without incorporating situation-based attentional requirements. Incorporating situation-based attentional requirements would entail an approach that not only considers the time spent looking elsewhere but also checks whether all necessary information has been sampled. METHOD: We assess the visual sampling requirements for the forward view based on 25 experienced drivers' self-paced visual occlusion in real motorway traffic, dependent on a combination of situational factors, and compare these with their corresponding glance behavior in baseline driving. RESULTS: Occlusion durations were on average 3 times longer than glances away from the forward roadway, and they varied substantially depending on particular maneuvers and on the proximity of other traffic, showing that interactions with nearby traffic increase perceived uncertainty. The frequency of glances away from the forward roadway was relatively stable across proximity levels and maneuvers, being very similar to what has been found in naturalistic driving. CONCLUSION: Glances away from the forward roadway proved qualitatively different from occlusions in both their duration and when they occur. Our findings indicate that glancing away from the forward roadway for driving purposes is not the same as glancing away for other purposes, and that neither is necessarily equivalent to distraction.

Performance of an Additional Task During Level 2 Automated Driving: An On-Road Study Comparing Drivers With and Without Experience With Partial Automation.

OBJECTIVE: To investigate the influence of prior experience with Level 2 automation on additional task performance during manual and Level 2 partially automated driving. BACKGROUND: Level 2 automation is now on the market, but its effects on driver behavior remain unclear. Based on previous studies, we could expect an increase in drivers' engagement in secondary tasks during Level 2 automated driving, but it is yet unknown how drivers will integrate all the ongoing demands in such situations. METHOD: Twenty-one drivers (12 without, 9 with Level 2 automation experience) drove on a highway manually and with Level 2 automation (exemplified by Volvo Pilot Assist generation 2; PA2) while performing an additional task. In half of the conditions, the task could be interrupted (self-paced), and in the other half, it could not (system-paced). Drivers' visual attention, additional task performance, and other compensatory strategies were analyzed. RESULTS: Driving with PA2 led to decreased scores in the additional task and more visual attention to the dashboard. In the self-paced condition, all drivers looked more to the task and perceived a lower mental demand. The drivers experienced with PA2 used the system and the task more than the novice group and performed more overtakings. CONCLUSIONS: The additional task interfered more with Level 2 automation than with manual driving. The drivers, particularly the automation novice drivers, used some compensatory strategies. APPLICATIONS: Automation designers need to consider these potential effects in the development of future automated systems.

Evaluation of methods for the assessment of attention while driving.

The ability to assess the current attentional state of the driver is important for many aspects of driving, not least in the field of partial automation for transfer of control between vehicle and driver. Knowledge about the driver's attentional state is also necessary for the assessment of the effects of additional tasks on attention. The objective of this paper is to evaluate different methods that can be used to assess attention, first theoretically, and then empirically in a controlled field study and in the laboratory. Six driving instructors participated in all experimental conditions of the study, delivering within-subjects data for all tested methods. Additional participants were recruited for some of the conditions. The test route consisted of 14km of motorway with low to moderate traffic, which was driven three times per participant per condition. The on-road conditions were: baseline, driving with eye tracking and self-paced visual occlusion, and driving while thinking aloud. The laboratory conditions were: Describing how attention should be distributed on a motorway, and thinking aloud while watching a video from the baseline drive. The results show that visual occlusion, especially in combination with eye tracking, was appropriate for assessing spare capacity. The think aloud protocol was appropriate to gain insight about the driver's actual mental representation of the situation at hand. Expert judgement in the laboratory was not reliable for the assessment of drivers' attentional distribution in traffic. Across all assessment techniques, it is evident that meaningful assessment of attention in a dynamic traffic situation can only be achieved when the infrastructure layout, surrounding road users, and intended manoeuvres are taken into account. This requires advanced instrumentation of the vehicle, and subsequent data reduction, analysis and interpretation are demanding. In conclusion, driver attention assessment in real traffic is a complex task, but a combination of visual occlusion, eye tracking and thinking aloud is a promising combination of methods to come further on the way.

Reduced Attention Allocation during Short Periods of Partially Automated Driving: An Event-Related Potentials Study.

Research on partially automated driving has revealed relevant problems with driving performance, particularly when drivers' intervention is required (e.g., take-over when automation fails). Mental fatigue has commonly been proposed to explain these effects after prolonged automated drives. However, performance problems have also been reported after just a few minutes of automated driving, indicating that other factors may also be involved. We hypothesize that, besides mental fatigue, an underload effect of partial automation may also affect driver attention. In this study, such potential effect was investigated during short periods of partially automated and manual driving and at different speeds. Subjective measures of mental demand and vigilance and performance to a secondary task (an auditory oddball task) were used to assess driver attention. Additionally, modulations of some specific attention-related event-related potentials (ERPs, N1 and P3 components) were investigated. The mental fatigue effects associated with the time on task were also evaluated by using the same measurements. Twenty participants drove in a fixed-base simulator while performing an auditory oddball task that elicited the ERPs. Six conditions were presented (5-6 min each) combining three speed levels (low, comfortable and high) and two automation levels (manual and partially automated). The results showed that, when driving partially automated, scores in subjective mental demand and P3 amplitudes were lower than in the manual conditions. Similarly, P3 amplitude and self-reported vigilance levels decreased with the time on task. Based on previous studies, these findings might reflect a reduction in drivers' attention resource allocation, presumably due to the underload effects of partial automation and to the mental fatigue associated with the time on task. Particularly, such underload effects on attention could explain the performance decrements after short periods of automated driving reported in other studies. However, further studies are needed to investigate this relationship in partial automation and in other automation levels.

Changes in glance behaviour when using a visual eco-driving system - A field study.

While in-vehicle eco-driving support systems have the potential to reduce greenhouse gas emissions and save fuel, they may also distract drivers, especially if the system makes use of a visual interface. The objective of this study is to investigate the visual behaviour of drivers interacting with such a system, implemented on a five-inch screen mounted above the middle console. Ten drivers participated in a real-world, on-road driving study where they drove a route nine times (2 pre-baseline drives, 5 treatment drives, 2 post-baseline drives). The route was 96 km long and consisted of rural roads, urban roads and a dual-lane motorway. The results show that drivers look at the system for 5-8% of the time, depending on road type, with a glance duration of about 0.6 s, and with 0.05% long glances (>2s) per kilometre. These figures are comparable to what was found for glances to the speedometer in this study. Glance behaviour away from the windscreen is slightly increased in treatment as compared to pre- and post-baseline, mirror glances decreased in treatment and post-baseline compared to pre-baseline, and speedometer glances increased compared to pre-baseline. The eco-driving support system provided continuous information interspersed with additional advice pop-ups (announced by a beep) and feedback pop-ups (no auditory cue). About 20% of sound initiated advice pop-ups were disregarded, and the remaining cases were usually looked at within the first two seconds. About 40% of the feedback pop-ups were disregarded. The amount of glances to the system immediately before the onset of a pop-up was clearly higher for feedback than for advice. All in all, the eco-driving support system under investigation is not likely to have a strong negative impact on glance behaviour. However, there is room for improvements. We recommend that eco-driving information is integrated with the speedometer, that optional activation of sound alerts for intermittent information is made available, and that the pop-up duration should be extended to facilitate self-regulation of information intake.

Minimum Required Attention: A Human-Centered Approach to Driver Inattention.

OBJECTIVE: To propose a driver attention theory based on the notion of driving as a satisficing and partially self-paced task and, within this framework, present a definition for driver inattention. BACKGROUND: Many definitions of driver inattention and distraction have been proposed, but they are difficult to operationalize, and they are either unreasonably strict and inflexible or suffer from hindsight bias. METHOD: Existing definitions of driver distraction are reviewed and their shortcomings identified. We then present the minimum required attention (MiRA) theory to overcome these shortcomings. Suggestions on how to operationalize MiRA are also presented. RESULTS: MiRA describes which role the attention of the driver plays in the shared "situation awareness of the traffic system." A driver is considered attentive when sampling sufficient information to meet the demands of the system, namely, that he or she fulfills the preconditions to be able to form and maintain a good enough mental representation of the situation. A driver should only be considered inattentive when information sampling is not sufficient, regardless of whether the driver is concurrently executing an additional task or not. CONCLUSIONS: The MiRA theory builds on well-established driver attention theories. It goes beyond available driver distraction definitions by first defining what a driver needs to be attentive to, being free from hindsight bias, and allowing the driver to adapt to the current demands of the traffic situation through satisficing and self-pacing. MiRA has the potential to provide the stepping stone for unbiased and operationalizable inattention detection and classification.

Vehicle-based studies of driving in the real world: the hard truth?

Real-world studies of driving behaviour and safety have face validity and have the distinct advantage of focussing on driving in its natural habitat. But their very naturalism can lead to problems with confounds and with noise in the data. This paper reviews the three major categories of on-road studies - controlled observation, field operational tests and naturalistic driving studies - and discusses the major applications of each study type. It also assesses some of the methodological issues that arise in one or more category of study.

Effects of electronic billboards on driver distraction.

OBJECTIVE: There is an increase in electronic advertising billboards along major roads, which may cause driver distraction due to the highly conspicuous design of the electronic billboards. Yet limited research on the impact of electronic billboards on driving performance and driver behavior is available. The Swedish Transport Administration recently approved the installation of 12 electronic billboards for a trial period along a 3-lane motorway with heavy traffic running through central Stockholm, Sweden. The aim of this study was to evaluate the effect of these electronic billboards on visual behavior and driving performance. METHOD: A total of 41 drivers were recruited to drive an instrumented vehicle passing 4 of the electronic billboards during day and night conditions. A driver was considered visually distracted when looking at a billboard continuously for more than 2 s or if the driver looked away from the road for a high percentage of time. Dependent variables were eye-tracking measures and driving performance measures. RESULTS: The visual behavior data showed that drivers had a significantly longer dwell time, a greater number of fixations, and longer maximum fixation duration when driving past an electronic billboard compared to other signs on the same road stretches. No differences were found for the factors day/night, and no effect was found for the driving behavior data. CONCLUSION: Electronic billboards have an effect on gaze behavior by attracting more and longer glances than regular traffic signs. Whether the electronic billboards attract too much attention and constitute a traffic safety hazard cannot be answered conclusively based on the present data.

Truck drivers' opinion on road safety in Tanzania--a questionnaire study.

OBJECTIVE: Even though the traffic fatality risk (fatalities per 100,000 inhabitants) in Tanzania is quite low, the fatality rate (fatalities per 10,000 vehicles) is one of the highest in the world. With increasing vehicle density this means that the number of people dying in traffic will increase dramatically in the near future. Therefore, it is important to implement measures to increase traffic safety as soon as possible, and in order to be able to do this in an efficient way, it is important to investigate where the main problems lie. METHODS: Within the European Union (EU) project ASSET-Road a questionnaire study on road safety was conducted with 250 truck drivers in Tanzania. The study was done to increase the knowledge about the situation of the Tanzanian truckers, who are the most frequent road users in the country. The drivers were interviewed in 3 different towns in southern Tanzania, and participation was voluntary. The questionnaire treated demographics, the state of the drivers' vehicles, the frequency of breakdowns, and the maintenance of the vehicles. Further questions concerned driver behavior, crash involvement, crash risk, and crash mitigation. RESULTS: The drivers who participated in the study were predominantly male and their average age was 36 years. Truck drivers reported driving 10.6 h without a break on average, with several drivers reporting that they had to drive 24 h without rest. Around 40 percent of the trucks did not have any seat belts installed, with a larger share of older trucks lacking belts. Most of the drivers who had seat belts reported using them, however. Almost 40 percent of the drivers reported being involved in at least one crash, and 45 percent of those drivers had experienced fatal crashes. This underlines that the crash frequency per vehicle is very high, and the results are often severe, especially when heavy vehicles are involved. When asked what the 3 most common crash causations were, driver-related causes were named frequently. Drivers were said to be reckless, and further crash causations named were drunkenness, inattention, and sleepiness. One of the most frequently mentioned crash mitigation strategies was driver education, followed by improvement of the roads and the vehicles. CONCLUSIONS: The results indicate that countermeasures should be implemented in an integrated fashion, taking into account aspects such as driver, vehicle, infrastructure, legislature, and other road users.

Measuring driver impairments: sleepiness, distraction, and workload.

Snow was falling heavily when Sarah was driving on a slippery road to her cousin's country cottage. It was dark outside, and the visibility was poor. She had planned to arrive before sunset, but the rental service had made a mistake, and it took hours before she got her rental car at the airport. It was past midnight now, and after a long day of traveling, Sarah was starting to get sleepy. Fortunately, there were only 15 km to go, but her eyelids were starting to feel heavy. To stay awake, she put her favorite CD on, turned up the volume, and started to sing along. This seemed to help a little-good-only 10 km to go. This was when Sarah's phone started ringing, and she awkwardly tried to find the mute button for the car stereo while answering the phone. As she looked up again, she barely caught a glimpse of the red brake lights of the car in front of her as she smashed into it.

The impact of tunnel design and lighting on the performance of attentive and visually distracted drivers.

The crash risk in tunnels is lower than on the open road network, but the consequences of a crash are often severe. Proper tunnel design is one measure to reduce the likelihood of crashes, and the objective of this work is to investigate how driving performance is influenced by design factors, and whether there is an interaction with secondary task load. Twenty-eight drivers participated in the simulator study. A full factorial within subject design was used to investigate the tunnel wall colour (dark or light-coloured walls), illumination (three different levels) and task load (with or without a visual secondary task). The results show that tunnel design and illumination have some influence on the drivers' behaviour, but visual attention given to the driving task is the most crucial factor, giving rise to significant changes in both driving behaviour and visual behaviour. The results also indicate that light-coloured tunnel walls are more important than strong illumination to keep the drivers' visual attention focused forward.

Predicting visual distraction using driving performance data.

Behavioral variables are often used as performance indicators (PIs) of visual or internal distraction induced by secondary tasks. The objective of this study is to investigate whether visual distraction can be predicted by driving performance PIs in a naturalistic setting. Visual distraction is here defined by a gaze based real-time distraction detection algorithm called AttenD. Seven drivers used an instrumented vehicle for one month each in a small scale field operational test. For each of the visual distraction events detected by AttenD, seven PIs such as steering wheel reversal rate and throttle hold were calculated. Corresponding data were also calculated for time periods during which the drivers were classified as attentive. For each PI, means between distracted and attentive states were calculated using t-tests for different time-window sizes (2 - 40 s), and the window width with the smallest resulting p-value was selected as optimal. Based on the optimized PIs, logistic regression was used to predict whether the drivers were attentive or distracted. The logistic regression resulted in predictions which were 76 % correct (sensitivity = 77 % and specificity = 76 %). The conclusion is that there is a relationship between behavioral variables and visual distraction, but the relationship is not strong enough to accurately predict visual driver distraction. Instead, behavioral PIs are probably best suited as complementary to eye tracking based algorithms in order to make them more accurate and robust.

Effects of road surface appearance and low friction warning systems on driver behaviour and confidence in the warning system.

Warning systems for slippery road conditions are a potential newcomer among driver support systems. A total of 75 participants drove in a high-fidelity driving simulator on roads with both visible and invisible ice, to investigate to which extent drivers rely on a low friction warning system. Three experimental groups with different versions of a low friction warning system and a control group without warning system were compared. All drivers ranked the systems according to trust. A system displaying recommended speed received the best ratings. Driving speed was analysed for three particular segments of the route. Generally, lowest speeds were achieved with the recommended speed system. The participants drove more slowly on a slippery segment that looked icy than on the segments that looked dry when they did not receive a low friction warning. When they received a warning for low friction they also lowered their speed for the segment looking like asphalt. The results provide guidelines for how to present low friction warnings to drivers. The design has substantial effects on the resulting behaviour and therefore it can have a high impact on traffic safety. So far, not much research on low friction warning systems has been reported.