What happens next? Predicting other road users' behaviour as a function of driving experience and processing time

Nudges may improve hazard perception in a contextual manner

This research investigates the effectiveness of nudge presentation on Hazard Perception (HP) during a computerized Hazard Perception Test (HPT). Three types of nudges were examined: Reminder, Social Norm, and Negative Reinforcement. Their effects on drivers' reaction times, hazard misidentifications (errors), and hazard recognition failures (misses) were analyzed. Additionally, the study explored how demographic and personality factors relate to individual differences in nudge responses. Results indicated that nudge presentation, regardless of type, improved reaction times and reduced errors. Reduction in errors was uniquely associated with personal characteristics, showing a positive correlation with age. Specifically, female participants and individuals low in conscientiousness exhibited fewer errors following the Social Norm nudge, while males and highly conscientious individuals showed reduced errors after the Reminder nudge. However, misses were unaffected by nudge presentation. All tested dependent variables were influenced by the order of hazard presentation, reflecting both contextual and nudge presentation effects. To further investigate the order's impact, a follow-up study examined specific hazards sensitive to nudge presentation. Findings revealed that some hazards were more influenced by nudge/contextual factors, while others were unaffected, highlighting the need to consider complex contextual dynamics in HP research. Overall, the study supports the conclusion that nudge presentation can positively influence HP without distracting drivers, offering a promising strategy for improving road safety.

Divergence in situation awareness and workload

Situation awareness (SA) and workload have both received considerable attention over the past several decades. Little research has investigated the relationship between these two constructs however. The present study examines the relationship between workload and SA in a task involving operation of unmanned vehicles performing an inspection task. Overall, an inverse correlation between SA and workload was found, with SA decreasing by approximately 20% as workload increased. Unexpectedly, considerable differences in this relationship across individuals were found, however, with 50% of participants showing a correlation between SA and only one workload measure (subjective or secondary task) and 30% showing no correlation between SA and workload on either measure. Reasons for dissociation within different measures of workload and SA are discussed, as well as potential reasons for individual differences leading to dissociations across these two constructs.

Pilot Study on Gaze Characteristics of Older Drivers While Watching Driving Movies

Objective: This study aims to clarify the gazing characteristics of older drivers while driving cars using a gaze analysis device. Methods: The participants included 16 older and 12 middle-aged drivers who drove cars daily. After conducting cognitive and attentional function tests, eye gaze while watching driving videos was measured using an eye tracker. Ten driving videos were prepared. In addition, a total of 34 hazard areas were analyzed. Results: The results of the gaze measurement parameters were statistically compared between the two groups. In the older group, the gaze analysis results indicated that while viewing driving videos, the search for areas close to the car was expanded. In addition, in several hazard areas, we observed a decrease in the number of drivers gazing at the driver, shortened total gazing time, delay in the timing of gazing, and decrease in the number of visits. Conclusions: Older drivers' eye movement is increased; however, it is characterized by gazing at unimportant areas, indicating an inefficient scanning pattern. Although these results do not indicate an obvious decline in driving ability among older drivers, the decline in hazard perception may become apparent in some situations. The data contain underpowered results and require revalidation in larger studies.

The efficacy of hazard perception training and education: A systematic review and meta-analysis

BACKGROUND

Hazard perception (HP) has been argued to improve with experience, with numerous training programs having been developed in an attempt to fast track the development of this critical safety skill. To date, there has been little synthesis of these methods.

OBJECTIVE

The present study sought to synthesise the literature for all road users to capture the breadth of methodologies and intervention types, and quantify their efficacy.

DATA SOURCES

A systematic review of both peer reviewed and non-peer-reviewed literature was completed. A total of 57 papers were found to have met inclusion criteria.

RESULTS

Research into hazard perception has focused primarily on drivers (with 42 studies), with a limited number of studies focusing on vulnerable road users, including motorcyclists (3 studies), cyclists (7 studies) and pedestrians (5 studies). Training was found to have a large significant effect on improving hazard perception skills for drivers (g = 0.78) and cyclists (g = 0.97), a moderate effect for pedestrians (g = 0.64) and small effect for motorcyclists (g = 0.42). There was considerable heterogeneity in the findings, with the efficacy of training varying as a function of the hazard perception skill being measured, the type of training enacted (active, passive or combined) and the number of sessions of training (single or multiple). Active training and single sessions were found to yield more consistent significant improvements in hazard perception.

CONCLUSIONS

This study found that HP training improved HP skill across all road user groups with generally moderate to large effects identified. HP training should employ a training method that actively engages the participants in the training task. Preliminary results suggest that a single session of training may be sufficient to improve HP skill however more research is needed into the delivery of these single sessions and long-term retention. Further research is also required to determine whether improvements in early-stage skills translate to improvements in responses on the road, and the long-term retention of the skills developed through training.

Road Hazard Stimuli: Annotated naturalistic road videos for studying hazard detection and scene perception

Driving requires vision, yet there is little empirical data about how vision and cognition support safe driving. It is difficult to study perception during natural driving because the experimental rigor required would be dangerous and unethical to implement on the road. The driving environment is complex, dynamic, and immensely variable, making it extremely challenging to accurately replicate in simulation. Our proposed solution is to study vision using stimuli which reflect this inherent complexity by using footage of real driving situations. To this end, we curated a set of 750 crowd-sourced video clips (434 hazard and 316 no-hazard clips), which have been spatially, temporally, and categorically annotated. These annotations describe where the hazard appears, what it is, and when it occurs. In addition, perceived dangerousness changes from moment to moment and is not a simple binary detection judgement. To capture this more granular aspect of our stimuli, we asked 48 observers to rate the perceived hazardousness of 1356 brief video clips taken from these 750 source clips on a continuous scale. These ratings span the entire scale, have high interrater agreement, and are robust to driving history. This novel stimulus set is not only useful for understanding drivers' ability to detect hazards, but is also a tool for studying dynamic scene perception and other aspects of visual function. While this stimulus set was originally designed for behavioral studies, researchers interested in other areas such as traffic safety or computer vision may also find this dataset a useful resource.

Knowing me, knowing you-A study on top-down requirements for compensatory scanning in drivers with homonymous visual field loss

OBJECTIVE

It is currently still unknown why some drivers with visual field loss can compensate well for their visual impairment while others adopt ineffective strategies. This paper contributes to the methodological investigation of the associated top-down mechanisms and aims at validating a theoretical model on the requirements for successful compensation among drivers with homonymous visual field loss.

METHODS

A driving simulator study was conducted with eight participants with homonymous visual field loss and eight participants with normal vision. Participants drove through an urban surrounding and experienced a baseline scenario and scenarios with visual precursors indicating increased likelihoods of crossing hazards. Novel measures for the assessment of the mental model of their visual abilities, the mental model of the driving scene and the perceived attention demand were developed and used to investigate the top-down mechanisms behind attention allocation and hazard avoidance.

RESULTS

Participants with an overestimation of their visual field size tended to prioritize their seeing side over their blind side both in subjective and objective measures. The mental model of the driving scene showed close relations to the subjective and actual attention allocation. While participants with homonymous visual field loss were less anticipatory in their usage of the visual precursors and showed poorer performances compared to participants with normal vision, the results indicate a stronger reliance on top-down mechanism for drivers with visual impairments. A subjective focus on the seeing side or on near peripheries more frequently led to bad performances in terms of collisions with crossing cyclists.

CONCLUSION

The study yielded promising indicators for the potential of novel measures to elucidate top-down mechanisms in drivers with homonymous visual field loss. Furthermore, the results largely support the model of requirements for successful compensatory scanning. The findings highlight the importance of individualized interventions and driver assistance systems tailored to address these mechanisms.

Simulator-based driving test prescreening as a complement to driver testing - Toward safer and more risk-aware drivers

Young people represent a high-risk group of drivers and the prevalence of road traffic crashes among young drivers is high. Thus, to increase traffic safety, it is essential to ensure that new drivers are both sufficiently educated in and assessed for risk awareness. The aim of this study was to examine the possibility and potential benefit of using a driving simulator screening test as a complement to the existing on-road driving test. The main idea is to detect drivers who are not ready to proceed to the driving test. A comparative study was performed with participants who passed and failed a simulator test and an on-road driving test, respectively. A comparison between subjective and objective measures of performance and risk was also included. A driving simulator was placed at a traffic school and customers were recruited as participants. In total, 70 participants took part in the study and the simulated drive consisted of rural roads, urban traffic, and motorways with 16 different scenarios, constructed from the second level of the GDE matrix, to examine driving behavior, attention, and risk perception. The results show that with a screening test in a driving simulator, it is possible to detect drivers who consider themselves ready to take a driving test, but who have not yet reached the level of risk awareness required to be a safe driver. Test scenarios should be suited to detect deficiencies in risk awareness, test different levels of the GDE matrix and, to complement the driving test, be difficult to assess in an on-road driving test. Deficiencies in self-evaluation that are well-known among young drivers are again confirmed. To practice self-evaluation, the driving simulator is suggested as a pedagogical tool, linked to the GDE matrix.

Effects of lane-change scenarios on lane-change decision and eye movement

Improper lane-change manoeuvre can cause traffic safety issues and even lead to serious traffic collisions. Quantifying the decision behaviour and eye movements can provide a deeper understanding of lane-change manoeuvre in vehicle interaction environment. The purpose of this study was to investigate the effect of lane-change scenarios defined by gaps on lane-change decision and eye movements. Twenty-eight participants were recruited to complete a naturalistic driving experiment. Eye movements and lane-change decision duration (LDD) were recorded and analysed. Results suggested that the scanning frequency (SF) and saccade duration (SD) were the sensitive parameters to respond to lane-change scenarios. LDD was significantly affected by the scenario, SF, and SD. The increase in LDD was related to the high difficulty gap and high frequency scanning of multiple regions. These findings evaluated the driver's decision performance in response to different lane-change environments and provided valuable information for measuring the driver's scenario perception ability.Practitioner summary: A naturalistic driving experiment was conducted to evaluate the interaction of lane-change decision, eye movement, and lane changing gap in a lane-change task. The results reveal the sensitive eye movement parameters to lane-change scenario, which provide guidelines for driver's perception ability test and professional driver assessment.

Optimization method to reduce the risky driving behaviors of ride-hailing drivers

INTRODUCTION

To promote the safety level of ride-hailing services, this study develops the Targeted and Differentiated Optimization Method of Risky Driving Behavior Education and Training (TDOM-RDBET) founded on driver type classification of high-risk drivers.

METHOD

Based on value and goal orientations, 689 drivers were classified into four driver types and were assigned to three groups, including an experimental group, a blank control group, and a general control group. This research preliminarily analyzes the effectiveness of the TDOM-RDBET to reduce mobile phone use while driving by assessing the main effects of the group and test session on the risk value ranking of mobile phone use while driving (AR), the frequency per 100 km of mobile phone use while driving (AF), and the frequency per 100 km of risky driving behaviors (AFR), as well as the interactive effects of the two factors on AR, AF, and AFR, based on a two-way analysis of variance (two-way ANOVA).

RESULTS

The results demonstrate an overall significant reduction in AR (F = 8.653, p = 0.003), AF (F = 11.027, p = 0.001), and AFR (F = 8.072, p = 0.005) for the experimental group after training. Moreover, significant interactive effects of the driver group × test session on AR (F = 7.481, p = 0.001) and AF (F = 15.217, p < 0.001) were found. AR was significantly lower for the experimental group than for the blank control group (p < 0.05) in the post-training condition. Moreover, AF was also significantly lower for the experimental group than for the blank control group (p < 0.05) and general control group (p < 0.05) in the post-training condition.

PRACTICAL APPLICATIONS

On the whole, it was preliminarily verified that the TDOM-RDBET is more effective than the general training method at modifying the risky driving behavior.

Anticipatory Driving in Automated Vehicles: The Effects of Driving Experience and Distraction

OBJECTIVE

To understand the influence of driving experience and distraction on drivers' anticipation of upcoming traffic events in automated vehicles.

BACKGROUND

In nonautomated vehicles, experienced drivers spend more time looking at cues that indicate upcoming traffic events compared with novices, and distracted drivers spend less time looking at these cues compared with nondistracted drivers. Further, pre-event actions (i.e., proactive control actions prior to traffic events) are more prevalent among experienced drivers and nondistracted drivers. However, there is a research gap on the combined effects of experience and distraction on driver anticipation in automated vehicles.

METHODS

A simulator experiment was conducted with 16 experienced and 16 novice drivers in a vehicle equipped with adaptive cruise control and lane-keeping assist systems (resulting in SAE Level 2 driving automation). Half of the participants in each experience group were provided with a self-paced primarily visual-manual secondary task.

RESULTS

Drivers with the task spent less time looking at cues and were less likely to perform anticipatory driving behaviors (i.e., pre-event actions or preparation for pre-event actions such as hovering fingers over the automation disengage button). Experienced drivers exhibited more anticipatory driving behaviors, but their attention toward the cues was similar to novices for both task conditions.

CONCLUSION

In line with nonautomated vehicle research, in automated vehicles, secondary task engagement impedes anticipation while driving experience facilitates anticipation.

APPLICATION

Though Level 2 automation can relieve drivers of manually controlling the vehicle and allow engagement in distractions, visual-manual distraction engagement can impede anticipatory driving and should be restricted.

Exploring hazard anticipation and stress while driving in light of defensive behavior theory

In driving, poor hazard anticipation would provide drivers less time to prepare an appropriate response, increasing the urgency of the situation and generating more stress. Assuming this, the current study seeks to determine whether a predictable road hazard triggers hazard anticipation in drivers that can mitigate the ensuing stress response, and whether the stress response is influenced by driving experience. In a simulated road environment, a cue was used to trigger hazard anticipation, and a road hazard to induce a stress response. Heart rate, pupil diameter, driving speed, subjective stress, arousal, and negative emotions, were retrieved from 36 drivers who all faced the cue followed by the hazard (i.e. a predictable hazard), the cue only, and the hazard only. In the light of work on defensive behaviors, the findings indicate that a predictable hazard triggers hazard anticipation detectable via (1) freezing behavior-characterized by cardiac deceleration-(2) anticipatory pupil dilation and (3) anticipatory speed deceleration. The results also point to a beneficial role for hazard anticipation in reducing driver stress, as evidenced by reductions in peak heart rate levels, as well as in reported levels of stress and negative emotions. Finally, the findings showed an influence of driving experience on reported levels of stress. Overall, this study shows how previous work on defensive behaviors can be used to gain insight into the processes and driving behaviors involved in hazard anticipation and stress.

Development of a hazard prediction test for Chinese cyclists and its association with crash involvement

Introduction

Hazard perception is the ability to sense the road environment and predict and respond to the upcoming dangerous events, and this factor is closely related to cyclists' crash involvement. However, due to a lack of valid instruments, studies concerning the hazard predictions and crashes of cyclists in China remain limited. This study attempted to develop a hazard prediction test for cyclists.

Method

The experiment presented 44 video clips filmed from cyclists' perspectives to 61 children aged 13-16 years and 119 adults aged 18-30 years. After the video clip displayed a black screen, participants were asked to answer the following questions: "What is the hazard?" (question 1), "Where is the hazard?" (question 2), and "What happens next?" (question 3). The differences in test scores between cyclists with high and low levels of experience, cyclists of different ages, and crash-involved and noncrash-involved cyclists were compared to examine the validity of the test.

Results

The final test contained 21 video clips and the internal consistency reliabilities of the three questions were satisfactory. Experienced cyclists are better able to identify and predict hazards than are cyclists with less experience, and adult cyclists have better hazard prediction abilities than child cyclists. More importantly, crash-involved cyclists receiving lower scores with respect to their ability to identify and predict hazards than noncrash-involved cyclists, thus indicating that the discriminant validity of the test was acceptable.

Practical applications

This newly-developed test exhibits acceptable reliability and validity and can be used as an effective tool to measure the hazard prediction abilities of cyclists with different ages and levels of experience in China. The natural driving videos and test in the study may hold promise for future practical applications, and the implications for road safety are discussed.

An online hazard prediction test demonstrates differences in the ability to identify hazardous situations between different driving groups

Previous research has found that the traditional approach to measuring hazard perception, as used by the UK Government, does not necessarily transfer well to other countries. The speeded response times of a hazard perception test were susceptible to threshold bias, differentiating drivers according to cultural background more than driving experience. An alternative method - the hazard prediction test - appears to mitigate these problems when used across different countries. The current study applies the hazard prediction methodology to a new cultural context (Israel), delivered via an online platform. A further innovation was to include both hazardous and non-hazardous trials allowing measures of criterion and sensitivity parameters of the Signal Detection Theory to be calculated.In total, 74 participants (43 experienced and 31 novices) watched 26 hazard prediction clips that had been filmed in Tel Aviv (Israel), 13 of which contained cues to genuine hazards. Each hazardous clip was occluded prior to the hazardous situation fully materialising, though with sufficient evidence that any participant who was looking in the right place at the right time would be able to correctly identify the unfolding hazard. Participants were first asked to identify whether there was a hazard (a binary decision), and then to predict how the traffic situation was going to develop by choosing one of four options provided after each video.As hypothesised, experienced drivers outperformed novices in the multiple-choice prediction question, provided that they had correctly identified that the clip contained a hazard in the first question. Novices were poor at selecting the correct multiple-choice option, regardless of whether they correctly identified that the clip contained a hazard. Both driving experience and hazard sensitivity significantly predicted multiple-choice accuracy, though criterion did not. The newly developed online test was successful in differentiating between experienced and novice driver groups for accuracy in prediction. These results support the roll-out of the hazard prediction methodology across different countries. Practitioner summary: This study provides new insights into how to develop an online hazard prediction test suitable for international export. The results suggest that this newly developed test is successful in differentiating between experienced and novice drivers. This raises the possibilit y of assessing and training drivers on a global scale.

Correlations among self-report, static image, and video-based hazard perception assessments: The validity of a new Lithuanian hazard prediction test

Scholars suggest that improving hazard perception (HP) skills among different road users can lead to safer driving. To this end, a small number of countries have developed a national hazard perception test for their licensing procedures. The purpose of the current research is to develop and validate a new video-based hazard prediction test for the Lithuanian driving context. Eighty-eight drivers participated in the study. Initially, 25 naturalistic clips were included and edited into a hazard prediction test following the "what happens next?" paradigm. The overall score of the test was higher for experienced drivers when compared with novices. On further inspection the overall group difference was driven by 12 clips. The Lithuanian Hazard Perception test HPT-LIT featuring static images (Tūskė et al., 2019) and Hazard Perception Questionnaire developed by White et al. (2011) were used to validate the new test. This new version of the test (12 clips, LHP₁₂) showed acceptable psychometric properties. Drivers with less driving experience demonstrated poorer hazard prediction skills than experienced drivers. The results revealed a negative correlation between hazard prediction scores on LHP₁₂ and crash involvement in the novice driver group, as well as a positive correlation between prediction scores and self-reported hazard prediction skills. It was concluded that the new Lithuanian hazard test shows potential for future research.

Toward a Theory of Visual Information Acquisition in Driving

OBJECTIVE

The aim of this study is to describe information acquisition theory, explaining how drivers acquire and represent the information they need.

BACKGROUND

While questions of what drivers are aware of underlie many questions in driver behavior, existing theories do not directly address how drivers in particular and observers in general acquire visual information. Understanding the mechanisms of information acquisition is necessary to build predictive models of drivers' representation of the world and can be applied beyond driving to a wide variety of visual tasks.

METHOD

We describe our theory of information acquisition, looking to questions in driver behavior and results from vision science research that speak to its constituent elements. We focus on the intersection of peripheral vision, visual attention, and eye movement planning and identify how an understanding of these visual mechanisms and processes in the context of information acquisition can inform more complete models of driver knowledge and state.

RESULTS

We set forth our theory of information acquisition, describing the gap in understanding that it fills and how existing questions in this space can be better understood using it.

CONCLUSION

Information acquisition theory provides a new and powerful way to study, model, and predict what drivers know about the world, reflecting our current understanding of visual mechanisms and enabling new theories, models, and applications.

APPLICATION

Using information acquisition theory to understand how drivers acquire, lose, and update their representation of the environment will aid development of driver assistance systems, semiautonomous vehicles, and road safety overall.

Improving Older Drivers’ Behaviors Using Theory of Planned Behavior

The proportion of older drivers has increased with the aging population. In order to improve the driving behavior and safety of older drivers, we aim to analyze behavior differences between older and younger drivers and then study an improvement strategy based on the older drivers’ behavioral characteristics. Older drivers’ behaviors can be enhanced through training, thereby improving driving safety. Simulated scenarios for behavior analysis and training are constructed for drivers who are recruited from the general driving population. Data on the drivers’ eye movement, physiological and psychological conditions, operation behavior, and vehicle status are collected and analyzed. The theory of planned behavior is adopted to construct a driving behavior enhancement training model for older drivers. Finally, a structural equation model is developed to comprehend the relationship between training level, driver characteristics, and traffic safety. The ability and speed of older drivers to obtain traffic information is worse than those of young and middle-aged drivers, and the vehicle control capability of older drivers has a larger volatility. The driving behavior training model can improve older drivers’ driving stability and safety, as follows: the positive effect of training on driving behavioral improvement is larger than the negative effect of aging; the negative effect of training level on dangerous driving tendency is larger than the positive effect of driver’s aging. The driving behavior of older drivers should be improved for the safety and stability of driving operations through the PNE (perceived-norm-execution) model. The relationship between training level, driving behavior characteristics, and traffic safety is discussed using the structural equation model, and results show that the training can improve the effect of the drivers’ age on the characteristics of driving behavior, and that older drivers tend to decrease dangerous driving tendencies.

Detecting driver stress and hazard anticipation using real-time cardiac measurement: A simulator study

OBJECTIVES

In the context of growing interest in real-time driver stress detection systems, we question the value of using heart rate change over short time periods to detect driver stress and hazard anticipation.

METHODS

To this end, we explored changes in heart rate and speed as well as perceived stress in 27 drivers in a driving simulator. Driver stress was triggered by using hazardous road events, while hazard anticipation was manipulated using three levels of hazard predictability: unpredictable (U), predictable (P), and predictable and familiar (PF).

RESULTS

The main results indicate that using heart rate change (1) is a good indicator for detecting driver stress in real time, (2) provides a cardiac signature of hazard anticipation, and (3) was affected by perceived stress groups. Further investigation is needed to validate the lack of relationship between increased anticipation/predictability and strengthened cardiac signature.

CONCLUSIONS

These results support the use of heart rate change as an indicator of real-time driver stress and hazard anticipation.

A context-aware driver model for determining recommended speed in blind intersection situations

The near-miss events involving vulnerable road users can lead to serious accidents. Safe and careful expert drivers perform a hazard-anticipatory driving and they will naturally seek to reduce the uncertainty by attempting to fit their current driving context into a pre-existing category they have already developed, that is, predicting what can happen. In this study, our target situation consists of a cyclist attempting a road crossing at a blind spot. This study aims at developing a context-aware driver model for determining the recommended driving speed at blind intersections based on the analysis of near-miss-incidence database, which includes the data on driver behavior and road environmental factors just before the near-miss. First, we extracted the drive-recorder data using the management tool provided in the database. Second, risk, which is defined as the time margin for drivers to perform evasive actions to avoid a crash, was quantified for the extracted data using the safety-cushion time. The safety-cushion time can be observed as a result of the driver's adjustment to the vehicle velocity depending on the given road environment. One of the key aspects in developing the context-aware driver model is to categorize the extracted near-miss data into two levels based on the risk quantifications: low- and high-risk events. The low- and high-risk events were regarded as a result of the driver's appropriate adjustment of, and inability or failure to adjust the vehicle velocity depending on the given road environment, respectively. Third, based on a multiple linear regression analysis with low-risk event dataset, we constructed a context-aware driver model to produce the recommended vehicle speed depending on the given road environment. The road environment variables, determined by stepwise regression, were identified as factors that reduced or increased the vehicle velocity at blind intersections, and were incorporated into the model as predictors. Furthermore, we quantitatively visualized drivers setting the baseline for speed adjustment and increasing or decreasing the speed according to the given road environment context. Fourth, the model validation demonstrated a coefficient of determination (R²) of 0.20, and a mean absolute error (MAE) of 6.54 km/h on average in the 5-fold cross-validation. Finally, to investigate the effectiveness of the constructed driver model on safety performance, we used the dataset of high-risk events as test data. Theoretically, the constructed driver model guided the drivers to drive the vehicle at the recommended speed, and thus convert more than half of the high-risk events into low-risk events. These results indicate that the context-aware driver model is feasible to be used to adjust the approaching speed at blind intersections in accordance with the road environment factors.

Identifying objective behavioural measures of expert driver situation awareness

Efforts to reduce road crash rates depend on a clear understanding of the factors that contribute to driver risk. Not all drivers are at equivalent risk. It is critical to identify the factors that contribute to the development of expertise in the driving environment. The rapid development of a driver's situation awareness (SA) is central to the safe performance of the driving task. Therefore, SA must be clearly operationalised in order to better assess its role in the development of expertise. This study employs an existing scheme based on the Perceptual Cycle Model (PCM) used for post hoc incident analysis and adapts it to the driving context. We attempted to correlate performance on coded verbalisations indicative of SA with non-invasive objective gaze metrics. Gaze metrics and the verbal counts were shown to differentiate between both expert and experienced (non-expert) drivers, but these measures failed to correlate with one another. Findings indicate differences in the way expert and experienced drivers update their schema of the driving task, with equivalent effort required to do so. The novel adaptation demonstrated in this paper allows for a domain-specific assessment of SA which reliably differentiates between drivers of varying expertise levels. Although selected gaze metrics were shown to be inadequate predictors of SA, additional analysis demonstrated key differences in gaze content. Combined, these findings enhance an understanding of expert SA development contributing to reduced crash risk.

The Multiple Object Avoidance (MOA) task measures attention for action: Evidence from driving and sport

Performance in everyday tasks, such as driving and sport, requires allocation of attention to task-relevant information and the ability to inhibit task-irrelevant information. Yet there are individual differences in this attentional function ability. This research investigates a novel task for measuring attention for action, called the Multiple Object Avoidance task (MOA), in its relation to the everyday tasks of driving and sport. The aim in Study 1 was to explore the efficacy of the MOA task to predict simulated driving behaviour and hazard perception. Whilst also investigating its test-retest reliability and how it correlates to self-report driving measures. We found that superior performance in the MOA task predicted simulated driving performance in complex environments and was superior at predicting performance compared to the Useful Field of View task. We found a moderate test-retest reliability and a correlation between the attentional lapses subscale of the Driving Behaviour Questionnaire. Study 2 investigated the discriminative power of the MOA in sport by exploring performance differences in those that do and do not play sports. We also investigated if the MOA shared attentional elements with other measures of visual attention commonly attributed to sporting expertise: Multiple Object Tracking (MOT) and cognitive processing speed. We found that those that played sports exhibited superior MOA performance and found a positive relationship between MOA performance and Multiple Object Tracking performance and cognitive processing speed. Collectively, this research highlights the utility of the MOA when investigating visual attention in everyday contexts.

Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender

Young novice drivers are more prone than older drivers to get involved in a risky driving situation. Some young drivers underestimate risk while overestimating their driving abilities, increasing the likelihood of engaging in risky behaviour. Age and inexperience both influence risk estimation, though it is not clear which of these variables is more important. Can drivers’ willingness to engage in risky behaviour be assessed in a similar way to hazard perception skill using video-based risky situations? The aim of the current study was to assess whether a video-based tool could measure the willingness to participate in risky driving situations and whether it can distinguish between different types of risky driving scenarios across gender and driver age groups. We also explored the moderating effect of age and gender on drivers’ experience in relation to the risky manoeuvres and participants’ willingness to engage in risky situations. Participants were presented with naturalistic videos from the perspective of the driver that contained active risky situations (result of driver’s own actions) and were asked to make a decision regarding a potential action (to overtake a bus/bicycle or pass through an amber light) and whether they would accelerate at this point. Participants reported that they were more willing to accelerate and overtake cyclists and buses and less willing to pass a light in amber. Young drivers were more willing to both engage in the risky behaviours and accelerate than older drivers, with young males reporting higher scores than the other groups. Gender differences were observed, with males being more prone to overtake and pass through a light in amber than females; however, this difference was not observed for the intention to accelerate. All the above effects remained when we tested the impact of experience on decision making while controlling for age and gender, although driving experience was no longer significant. These results demonstrate that drivers’ intention to assume risk can indeed be measured in a similar video-based methodology to that used by hazard perception tests. The findings raise the possibility of assessing and training drivers on a wider range of safety-related behaviours.

Situation Awareness Measurement in Remotely Controlled Cars

This study reviews the current information concerning the measurement of the situation awareness (SA) of the teleoperated drivers of remotely controlled cars. The teleoperated drivers who drive these cars are in a remote location, and they control the cars through a communication interface. The objective methods with probes are beneficial in measuring SA on a closed circuit without real traffic. Questions specifically should address the information provided on the road by haptic sensations, such as the slope of the road and the vehicle's speed. Methods for measuring SA that involve probes and interruptions obviously are not suitable for use on public roads. A stable environment for the display and control of the communication interface is suitable for an eye tracker in measuring SA. These features also facilitate the use of subjective observer-rating methods. Both of these methods are suitable for driving on real roads because they are not intrusive. SA research in a real-road environment also should demonstrate how the SA of other drivers is affected by seeing a car without a driver. Given the remote character of driving, cultural differences in cognition may have a significant influence on the SA of the teleoperated driver.

A Systematic Review and Meta-Analysis of Direct Objective Measures of Situation Awareness: A Comparison of SAGAT and SPAM

OBJECTIVE

To examine evidence of sensitivity, predictiveness, and methodological concerns regarding direct, objective measures of situation awareness (SA).

BACKGROUND

The ability to objectively measure SA is important to the evaluation of user interfaces and displays, training programs, and automation initiatives, as well as for studies that seek to better understand SA in both individuals and teams. A number of methodological criticisms have been raised creating significant confusion in the research field.

METHOD

A meta-analysis of 243 studies was conducted to examine evidence of sensitivity and predictiveness, and to address methodological questions regarding Situation Awareness Global Assessment Technique (SAGAT), Situation Present Assessment Technique (SPAM), and their variants.

RESULTS

SAGAT and SPAM were found to be equally predictive of performance. SPAM (64%) and real-time probes (73%) were found to have significantly lower sensitivity in comparison to SAGAT (94%). While SAGAT was found not to be overly memory reliant nor intrusive into operator performance, SPAM resulted in problems with intrusiveness in 40% of the studies examined, as well as problems with speed-accuracy tradeoffs, sampling bias, and confounds with workload. Concerns about memory reliance, the utility of these measures for assessing Team SA, and other issues are also addressed.

CONCLUSION

SAGAT was found to be a highly sensitive, reliable, and predictive measure of SA that is useful across a wide variety of domains and experimental settings.

APPLICATION

Direct, objective SA measurement provides useful and diagnostic insights for research and design in a wide variety of domains and study objectives.

Development and validity of a hazard prediction test for Chinese drivers

Background

Hazard perception ability, which develops with driving experience, has been proven to be associated with drivers' traffic involvement. Although classic reaction time-based hazard perception tests have been developed in many developed counties, experience-related differences may not be found in drivers from developing countries due to their increased opportunities to experience hazards on roads. Therefore, the present study aims to develop a hazard prediction test for Chinese drivers based on a predictive paradigm called “What happens next?” and assess its reliability and validity.

Method

Thirty-six video clips filmed from drivers’ perspectives of Chinese driving settings were presented to 54 novice drivers and 47 experienced drivers. Participants were asked to answer three questions after each video clip was blacked out and to then quickly press the mouse button on a reaction time-based hazard perception test. Both the differences in the test scores between novice and experienced drivers and the differences in scores between drivers with and without traffic violations were compared.

Results

The final hazard prediction test consisted of 20 video clips. A high internal consistency coefficient of the test, i.e., Cronbach's alpha = 0.862, was obtained. The total scores of the test were positively and significantly correlated with reaction times as measured on the video-based hazard perception test, thus providing evidence regarding the discriminant validity of the test. More importantly, drivers with traffic violations obtained significantly lower total scores on the test than did drivers without traffic violations.

Conclusion

The newly developed hazard prediction test exhibited adequate psychometric properties and provided a practical alternative for assessing drivers’ hazard perception ability in China.

A novel driving assessment combining hazard perception, hazard prediction and theory questions

A new hazard test was created using high-fidelity computer animation containing ten hazards. Sixty learner drivers and sixty experienced drivers sat either a hazard-perception version of this test (requiring timed responses to materialized hazards) or a hazard-prediction variant of the test (where the screen is occluded as the hazard begins to appear and drivers are asked 'What happens next?'). Recent studies have demonstrated that the prediction test format outperforms the hazard perception format using naturalistic video, but there has not yet been a study replicating this effect with computer-animated materials similar to the quality of those used in the official UK hazard perception test. The new test also included eleven theory questions designed to probe drivers' knowledge of the rules of the road. The results demonstrated that both test variants differentiated between driver groups with considerable effect sizes. Theory-question scores were comparable across learner and experienced driver groups, reflecting learners' preparation for the test and possible issues with memory decay and overwriting in the experienced group. As an interesting aside, driving-related video game play negatively correlated with hazard perception performance, but not with hazard prediction scores. Some individual hazards better suited the prediction or perception test format, raising the possibility of a future hybrid test that combines the two approaches.

Visual attention in realistic driving situations: Attentional capture and hazard prediction

In real life, many objects catch our attention involuntarily or exogenously. Exogenous attention occurs fast and its effects are short-lived. In the laboratory, when attentional orientation is studied, both valid and invalid attentional signals are used: the valid ones direct the attention to a location where something relevant is going to appear. The invalid ones occur in a location where nothing relevant is going to happen. Usually, performance is improved when valid signals rather than invalid ones are presented. This work is novel in that it explores the effects of attentional capture and driving experience in situations of day-to-day driving while participants carry out a Hazard Prediction task. We created new Hazard Prediction (HPr) and Risk Estimation (RE) tests when driving by selecting 48 short videos recorded in a realistic way from the perspective of a car driver. We created valid and invalid trials by selecting videos in which a what?? was presented in the same spatial location as the one where the hazard was beginning to develop or in a different location. Simple situations, with only one developing hazard, were also presented. A total of 92 participants (30 experienced drivers, 32 novices and 30 with no experience) were placed in the position of the driver and answered the questions: 1) What will happen after the video is cut? 2) To what extent do you consider this situation risky? The results from the Hazard Prediction test replicate the attentional capture effect in complex driving situations, with invalid trials obtaining the worst results, followed by valid and simple ones. Participants with experience obtained better scores than novices, and novices were better than drivers without experience. No interaction between attentional orientation and experience was found, suggesting the obligatory and automatic nature of orientation processes, which do not appear to be compensated for by driving experience. No significant differences were found for the Risk Estimation test.

Important Aspects of Human Behavior in Road Traffic Accidents

Worldwide road traffic accidents have been increasing. Human behaviors and environmental factors are often responsible for such events. This being a serious public health concern, public health interventions are needed to minimize the rate of road traffic accidents. We aimed to identify broader human behaviors, sociodemographic factors, and environmental factors associated with the risk of road traffic accidents. We searched for the relevant studies in electronic database including PubMed, Cochrane, Web of Science, Google Scholar, and World Health Organization global health library. In addition, a manual search was also performed. Findings from scientific literature were presented in a summative form. Young age, male gender, speed, influence of substance, use of mobile phone, driving experience, temperament, attitude, aggression, stress, anxiety, emotionality, fatigue, lack of sleep, and road conditions were found closely associated with a risk of road traffic accidents. Despite having substantial driving training and ability to handling motor vehicles, professional drivers such as bus and taxi drivers are very vulnerable to road traffic accidents. This study reports that the increasing prevalence of road traffic accidents can be addressed significantly by applying behavior change theories. The health belief model was found useful in promoting safer driving.

Studying Gaze Behavior to Compare Three Different Hazard Perception Tasks

OBJECTIVE

The aim of the current study was to compare the traditional, verbal, and motoric tasks regarding their contributions to hazard perception measurement.

BACKGROUND

Traditional hazard perception tasks require the participants to respond to filmed traffic conflicts in an imprecise way, such as by pressing a button. More sophisticated tasks include either verbal specification or motoric localization of the perceived hazards. The present study investigated the participants' gaze behavior when they were provided with an identical set of traffic animations but were instructed to perform one of three types of hazard perception tasks.

METHOD

In an eye tracking study, 69 drivers were shown animated traffic scenarios and instructed to perform the traditional (press button), verbal, or speeded motoric localization hazard perception task. Eye tracking revealed whether and when the participant had fixated a certain hazard cue.

RESULTS

The participants in the traditional task group were slower to fixate emerging hazards, but quicker to respond to them than the participants of the verbal and the motoric groups. As a specific benefit, the verbal task differentiated between different types of failures.

CONCLUSION

Additional verbal or speeded motoric localization tasks seem to have increased the participants' alertness when watching the animations. The verbal task provides valuable additional information regarding the participants' performance. To approximate real-life hazard perception ability, it is recommended that researchers and practitioners use a combination of different hazard perception tasks for assessment and training.

Hazard Perception and Prediction test for walking, riding a bike and driving a car: "Understanding of the global traffic situation"

To "put oneself in the place of other road users" may improve understanding of the global traffic situation. It should be useful enabling drivers to anticipate and detect obstacles in time to prevent accidents to other road users, especially those most vulnerable. We created a pioneering Hazard Perception and Prediction test to explore this skill in different road users (pedestrians, cyclists and drivers), with videos recorded in naturalistic scenarios: walking, riding a bicycle and driving a car. There were 79 participants (30 pedestrians, 14 cyclists, 13 novice drivers and 22 experienced drivers). Sixty videos of hazardous traffic situations were presented, divided into 2 blocks of 30 videos each: 10 walking, 10 riding a bicycle, 10 driving a car. In each situation presented, we evaluated the performance of the participants carrying out the task of predicting the hazard and estimating the risk. In the second block, after they had carried out the task, we gave them feedback on their performance and let them see the whole video (i.e., checking what happened next). The results showed that the holistic test had acceptable psychometric properties (Cronbach's alpha = .846). The test was able to discriminate between the different conditions manipulated: a) between traffic hazards recorded from different perspectives: walking, riding a bicycle and driving a car; b) between participants with different user profiles: pedestrians, cyclists and drivers; c) between the two test blocks: the first evaluation only and the second combining evaluation with this complex intervention. We found modal bias effects in both Hazard Perception and Prediction; and in Risk Estimation.

Expert Drivers' Prospective Thinking-Aloud to Enhance Automated Driving Technologies - Investigating Uncertainty and Anticipation in Traffic

Current automated driving technology cannot cope in numerous conditions that are basic daily driving situations for human drivers. Previous studies show that profound understanding of human drivers' capability to interpret and anticipate traffic situations is required in order to provide similar capacities for automated driving technologies. There is currently not enough a priori understanding of these anticipatory capacities for safe driving applicable to any given driving situation. To enable the development of safer, more economical, and more comfortable automated driving experience, expert drivers' anticipations and related uncertainties were studied on public roads. First, driving instructors' expertise in anticipating traffic situations was validated with a hazard prediction test. Then, selected driving instructors drove in real traffic while thinking aloud anticipations of unfolding events. The results indicate sources of uncertainty and related adaptive and social behaviors in specific traffic situations and environments. In addition, the applicability of these anticipatory capabilities to current automated driving technology is discussed. The presented method and results can be utilized to enhance automated driving technologies by indicating their potential limitations and may enable improved situation awareness for automated vehicles. Furthermore, the produced data can be utilized for recognizing such upcoming situations, in which the human should take over the vehicle, to enable timely take-over requests.

Creating a hazard-based training and assessment tool for emergency response drivers

Emergency response drivers (ERDs) are often required to engage in high-risk driving manoeuvres on their way to a reported incident. Such risk requires that these drivers receive a high-level of training and continued development. The aim of this paper was to investigate an innovative format for a new potential tool that could support the training and assessment of these drivers: a single-clip Holistic Hazard Test, containing multiple hazards in a single route. In study one, we created a proof-of-concept 15-minute clip containing hazards, multiple-choice questions and probes to collect self-reported safety ratings. ERDs were more accurate on the multiple-choice questions (MCQs) than a control group, though response time scores to hazards did not reach the threshold for significance. In study two, we refined the development process and created a series of new holistic hazard tests across four counties of the East Midlands, UK. Each test contained many hazards and MCQs that assessed situation awareness and decision-making, based on the results of study 1. Participants were recruited across the four counties and were presented with both the test that was specific to their county and one of the unfamiliar-location tests, in order to assess the generalisability of the tests across different locales. The results showed no differences regarding location familiarity, suggesting that tests filmed in one area of the country can be viewed by drivers elsewhere without detriment to performance. ERDs once again responded to MCQs more accurately, and also scored more hazard points on the basis of faster responses to hazards compared to control participants. These results suggest such tests can successfully tap into ERD-specific skills with regard to spotting, predicting and responding to hazards on the road. We recommend refinement of this tool for assessment of emergency response drivers, and further development to extend the materials to create a training tool.

Structural Equation Modeling of Drivers' Situation Awareness Considering Road and Driver Factors

Driver’s situation awareness (SA) is one of the key elements that affect driving decision-making and driving behavior. SA is influenced by many factors, and previous studies have focused only on individual factors. This study presents a comprehensive study to explore the path relationships and influence mechanism between SA and all influential factors, including road characteristics, driver characteristics and states, distracting elements, and cognitive ability. A structural equation model that relates SA to its influential factors is developed. A total of 324 valid questionnaires were collected to analyze and identify the relationships between the factors. The results show that the preceding influential factors have significant effects on SA, which is consistent with previous research. Based on path coefficients, positive effects were: cognitive abilities (0.500), driver state (0.360), age (0.277), driving experience (0.198), and gender (0.156). Negative effects were: distracting elements (−0.253) and road characteristics (−0.213). The results of this comprehensive study provide a valuable reference for the development of driver training programs and driving regulations.

Does the use of a head mounted display increase the success of risk awareness and perception training (RAPT) for drivers?

The PC-based driver training programme, Risk Awareness and Perception Training (RAPT) has been successful in improving young drivers' hazard anticipation and mitigation responses in both simulator and on-road studies. The current research aimed to evaluate the success of an adaptation of this training for the UK context, along with investigating the impact of the presentation modality on RAPT effectiveness. Traditionally RAPT has been delivered on a PC monitor, which does not allow the same range of head and eye movements that drivers use when on the road. Thus, it was anticipated that the 360° field-of-view provided by Head Mounted Display (HMD) technology would provide a more ecologically valid experience, facilitating deeper processing and encoding of driving relevant scanning patterns, and an increased capacity to identify potentially hazardous areas of a driving scenario. Using a between-subjects design, three different training modalities were compared - a PC-based version using still images (PC-Stills), a HMD version using still images (HMD-Stills), and a HMD version using videos (HMD-video). All three training groups' performance on the UK Hazard Perception test was compared to that of a control group, who received no training. Results indicated that the adaptation of the training materials for the UK context was successful, with all three training programmes leading to performance improvements in the RAPT tests. Although participants in the HMD-video condition required more attempts to pass the training, this group showed the greatest improvement in hazard perception scores from the pre- to the post-training tests. Results also showed scenario-based differences between the modalities, suggesting that the success of different versions of RAPT may be linked to the type of risky scenario being targeted.

Predicting road scenes from brief views of driving video

If a vehicle is driving itself and asks the driver to take over, how much time does the driver need to comprehend the scene and respond appropriately? Previous work on natural-scene perception suggests that observers quickly acquire the gist, but gist-level understanding may not be sufficient to enable action. The moving road environment cannot be studied with static images alone, and safe driving requires anticipating future events. We performed two experiments to examine how quickly subjects could perceive the road scenes they viewed and make predictions based on their mental representations of the scenes. In both experiments, subjects performed a temporal-order prediction task, in which they viewed brief segments of road video and indicated which of two still frames would come next after the end of the video. By varying the duration of the previewed video clip, we determined the viewing duration required for accurate prediction of recorded road scenes. We performed an initial experiment on Mechanical Turk to explore the space, and a follow-up experiment in the lab to address questions of road type and stimulus discriminability. Our results suggest that representations which enable prediction can be developed from brief views of a road scene, and that different road environments (e.g., city versus highway driving) have a significant impact on the viewing durations drivers require to make accurate predictions of upcoming scenes.

Driving automation state-of-mind: Using training to instigate rapid mental model development

The automotive industry is chugging along towards full autonomy, with a yet unknown time of arrival. The next call, however, is partial driving automation. At this interim station lurks many dangers, there-among them issues surrounding the partial performance of the driving task. Despite their potential for increased safety, these systems come with many inherent limitations and caveats, and their safe use depend on drivers correctly understanding their new role. Training is proposed as a potentially effective method of introducing drivers to the central aspects in this human-automation interaction. A proof-of-concept training program designed to introduce drivers to a partial automation system was developed. The effects of training were then evaluated through a between-group mixed-methods simulator experiment. Results indicate that trained drivers both self-report and exhibit an improved understanding of the automation system. They also report a significantly higher inclination to retake control in critical situation, than do their untrained counterparts.

How are distractibility and hazard prediction in driving related? Role of driving experience as moderating factor

Distraction constitute one of the 'five fatal' behaviours that contribute to road trauma, and some people may be more susceptible to it than others. It is also known that a greater ability to predict danger is related to a lower probability of suffering accidents. It could be hypothesised that drivers with a higher tendency to distraction are worse at predicting traffic hazards, but to what extent might driving experience serve to mitigate this tendency to distraction? The current study collected self-reported attentional errors from drivers by using the Attention-Related Driving Errors Scale (ARDES-Spain) in order to examine whether novice drivers suffered from inattention more than experienced drivers. The results demonstrated that novice drivers scored more highly on ARDES than experienced drivers. ARDES scores were then related to performance in a Hazard Prediction test, where participants had to report what hazard was about to happen in a series of video clips that occlude just as the hazard begins to develop. While experienced drivers were better at the Hazard Prediction test than novice drivers, those participants who reported fewer attention errors were also better able to detect the upcoming hazard following occlusion. In addition, our results demonstrate a relationship between self-reported attentional errors and the ability to predict upcoming hazards on the road, with driving experience having a moderating role. In the case of novice drivers, as their scores in the Manoeuvring Errors ARDES factor increase, their ability in Hazard Prediction diminishes, while for experienced drivers the increase is not significant. Guidance on how to improve training for drivers in order to mitigate the effects of inattention on driving safety can be addressed.

Eye glances towards conflict-relevant cues: the roles of anticipatory competence and driver experience

OBJECTIVE

This paper analyzes the effects of anticipatory competence and driver experience on glance patterns towards visual cues that indicate conflict situations.

BACKGROUND

Prior research has shown that experienced drivers' visual scanning patterns differ from those of novices. Experienced drivers are less erratic and more systematic in their monitoring of the environment. We have also shown in an earlier study that driving experience improves anticipatory competence in that it leads to a higher number of timely proactive actions in conflict-scenarios (avoidance actions prior to, as opposed to in reaction to a conflict). This paper investigates glance patterns specifically to relevant visual cues in conflict scenarios to determine whether glance patterns of anticipatory drivers who exhibit proactive actions differ from those who do not. It also investigates whether experienced drivers pay more attention to these cues compared to novices.

METHOD

We conducted a simulator experiment with 24 experienced and 24 novice drivers. As part of the experiment, all drivers completed three distinct traffic scenarios, each with a conflict situation.

RESULTS

The results show that drivers who exhibited proactive actions had more frequent and longer glances towards conflict-relevant cues than those who did not exhibit any. Similarly, experienced drivers focused on these visual cues more often, and for longer durations compared to novices. Further, experienced drivers who exhibited proactive actions looked at the cues more often compared to experienced drivers who did not exhibit any; there was no significant difference for novice drivers.

CONCLUSION

These findings speak to the role of situation-specific visual cues for anticipatory competence, and to the importance of driver experience to aid in the interpretation of these cues. Future research should seek to confirm our findings in a wider variety of driving scenarios.

Road user hazard perception tests: A systematic review of current methodologies

BACKGROUND

Poor hazard perception, or the ability to anticipate potentially dangerous road and traffic situations, has been linked to an increased crash risk. Novice and younger road users are typically poorer at hazard perception than experienced and older road users. Road traffic authorities have recognised the importance of hazard perception skills, with the inclusion of a hazard perception test in most Graduated Driver Licensing (GDL) systems.

OBJECTIVES

This review synthesises studies of hazard perception tests in order to determine best practice methodologies that discriminate between novice/younger and experienced/older road users.

DATA SOURCES

Published studies available on PsychInfo, Scopus and Medline as at April 2018 were included in the review. Studies included a hazard perception test methodology and compared non-clinical populations of road users (car drivers, motorcyclists, bicyclists and pedestrians), based on age and experience, or compared methodologies.

RESULTS

49 studies met the inclusion criteria. There was a high degree of heterogeneity in the studies. However all methodologies - video, static image, simulator and real-world test-drive were able to discriminate road user groups categorised by age and/or experience, on at least one measure of hazard perception.

CONCLUSIONS

Whilst there was a high level of heterogeneity of studies, video methodology utilising temporal responses (e.g. press a button when detecting the potential hazard) are a consistent measure of hazard perception across road user groups, whereas spatial measures (e.g. locate potential hazard in the scenario) were inconsistent. Staged footage was found to discriminate as well as unstaged footage, with static images also adding valuable information on hazard perception. There were considerable inconsistencies in the categorising of participants based on age and experience, limited application of theoretical frameworks, and a considerable lack of detail regarding post hoc amendments of hazardous scenarios. This research can guide further developments in hazard perception testing that may improve driver licensing and outcomes for road users.

Safety Culture among Private and Professional Drivers in Norway and Greece: Examining the Influence of National Road Safety Culture

While Norway had the lowest road mortality rate in Europe in 2017, Greece had one of the worst road safety records of all EU-27 countries. The present study investigates road safety culture (RSC) as an explanation for this discrepancy by: (1) Comparing the road safety behaviours among professional and private drivers in Norway and Greece, (2) Examining factors influencing road safety behaviours, focusing especially on national road safety culture, and (3) Examining the influence of road safety behaviours and other factors (e.g., demographic and work-related variables) on accident involvement. This is done by comparing survey answers of private car (N = 796) and professional drivers (heavy goods vehicles and buses) in Norway and Greece (N = 416). Results from qualitative interviews (N = 61) are also presented. We study safety behaviours hypothesized to vary according to nationality (e.g., aggressive violations), and behaviours hypothesized to vary according to the professional versus private driver dimension (e.g., seat belt use). A central objective is to examine whether the former safety behaviours are more similar among private and professional drivers within countries than among professional and private drivers across national samples, indicating common national road safety cultures among private and professional drivers in the respective countries. The results indicate that aggressive violations are more similar among private and professional drivers within the national samples, than across the national samples, while seat belt use seems to vary according to the professional versus private dimension. The results also indicate a relationship between aggressive violations and accident involvement, although other variables were more strongly correlated. Moreover, drivers’ safety behaviours were influenced by the behaviours that these groups ascribed to other drivers in their countries, indicating the existence of different national road safety cultures. The Greek RSC was characterized by more aggression and violations than the Norwegian RSC, which seemed to be characterized by a higher level of compliance and politeness. The different RSCs may perhaps shed light on the different accident records in the two countries.

Effects of hazard types on drivers' risk rating and hazard response in a video-based hazard perception task

Hazard perception is crucial for identifying potential hazards on the road, and how quick drivers can respond to the hazard partially relies on their risk rating of the hazard after they detect it. Although many studies have attempted to reveal the relationship between drivers’ response latencies and their risk ratings, this relationship has not been extensively explored under different hazard types. The present study addresses this issue using a video-based hazard perception task. Forty novice drivers and 35 experienced drivers were recruited and 26 video clips containing either an overt hazard (continuous visibility) or a covert hazard (interrupted visibility) were shown to participants. Participants were asked to finish the hazard perception task first and then rated the risk level of the hazard when each video clip was replayed. Participants’ confidence in their answers for risk ratings was also determined. Results showed that experienced drivers responded to overt and covert hazards faster than did novice drivers. A negative and significant correlation was found between drivers’ risk ratings of covert hazards and their response latencies. Such a relationship was not found for overt hazards. More importantly, drivers rated the risk level of covert hazards higher than that of overt hazards, and higher risk ratings of covert hazards resulted in faster responses to these hazards. The findings of the present study indicate that hazard types not only influence drivers’ risk ratings and response latencies but also determine their relationships.

Modeling and mitigating fatigue-related accident risk of taxi drivers

Taxi drivers worldwide often have very long driving hours and experience frequent fatigue. These conditions are associated with a high prevalence of fatigue and accidents. However, the key factors that distinguish high/low fatigue-related accident risk (FRAR) taxi drivers are uncertain. By examining a series of potential factors related with fatigue or accident risk as discussed in previous research, the objective was to find out the most important factors that relate to taxi driver's FRAR, and to investigate the association of these factors and taxi driver's FRAR. Modeling methods were applied to questionnaire data collected from Beijing taxi drivers. A 269-sample dataset was analyzed to identify key factors related to FRAR and to fit FRAR prediction models. The model's performance on high-risk driver prediction was then tested using another independently collected 100-sample dataset. High-risk taxi drivers had significantly longer driving hours per working day, lower rest ratios, less driving experience, and were more confident about their fatigue resistance. The FRAR model with only four major measurable predictors achieved a sensitivity of 91.9% and a specificity of 94.6% on predicting labeled data. Adjusting drive-rest habits and self-evaluation pertaining to these predictors is good for high-risk drivers to mitigate their accident risk. It was concluded that taxi drivers' drive-rest habits, experience, and intention for fatigue driving are crucial, and to a large degree determine their FRAR, and the prediction model can satisfactorily identify high-risk taxi drivers.

A comparison of hazard perception and hazard prediction tests across China, Spain and the UK

Hazard perception (HP) is the ability to spot on-road hazards in time to avoid a collision. This skill is traditionally measured by recording response times to hazards in video clips of driving, with safer, experienced drivers often out-performing inexperienced drivers. This study assessed whether HP test performance is culturally specific by comparing Chinese, Spanish and UK drivers who watched clips filmed in all three countries. Two test-variants were created: a traditional HP test (requiring timed hazard responses), and a hazard prediction test, where the film is occluded at hazard-onset and participants predict what happens next. More than 300 participants, across the 3 countries, were divided into experienced and inexperienced-driver groups. The traditional HP test did not discriminate between experienced and inexperienced drivers, though participant nationality influenced the results with UK drivers reporting more hazards than Chinese drivers. The hazard prediction test, however, found experienced drivers to out-perform inexperienced drivers. No differences were found for nationality, with all nationalities being equally skilled at predicting hazards. The results suggest that drivers' criterion level for responding to hazards is culturally sensitive, though their ability to predict hazards is not. We argue that the more robust, culturally-agnostic, hazard prediction test appears better suited for global export.

Study of driving skill level discrimination based on human physiological signal characteristics

The primary purpose of the study is to distinguish the differences in driving skill between novice and experienced drivers from the viewpoint of human cognitive behavior. Firstly, EEG (electroencephalogram) signals were collected using EEG acquisition equipment called Neuroscan. The δ sub-band and EOG (electrooculogram) signals were extracted from the EEG. Furthermore, the eye movement rate and the sample entropy (SampEn) values of δ sub-bands were calculated. Finally, the heart rate variability (HRV) characteristics, calculated using the SampEn algorithm, were used to analyze driving skill. The final result showed that human physiological signals (EEG, EOG and ECG (electrocardiogram)) could effectively distinguish different driving skills.

Prediction and perception of hazards in professional drivers: Does hazard perception skill differ between safe and less-safe fire-appliance drivers?

Can hazard perception testing be useful for the emergency services? Previous research has found emergency response drivers' (ERDs) to perform better than controls, however these studies used clips of normal driving. In contrast, the current study filmed footage from a fire-appliance on blue-light training runs through Nottinghamshire, and endeavoured to discriminate between different groups of EDRs based on experience and collision risk. Thirty clips were selected to create two variants of the hazard perception test: a traditional push-button test requiring speeded-responses to hazards, and a prediction test that occludes at hazard onset and provides four possible outcomes for participants to choose between. Three groups of fire-appliance drivers (novices, low-risk experienced and high-risk experienced), and age-matched controls undertook both tests. The hazard perception test only discriminated between controls and all FA drivers, whereas the hazard prediction test was more sensitive, discriminating between high and low-risk experienced fire appliance drivers. Eye movement analyses suggest that the low-risk drivers were better at prioritising the hazardous precursors, leading to better predictive accuracy. These results pave the way for future assessment and training tools to supplement emergency response driver training, while supporting the growing literature that identifies hazard prediction as a more robust measure of driver safety than traditional hazard perception tests.

The Effects of Distraction on Anticipatory Driving

The anticipation of future events in traffic can allow potential gains in recognition and response times. Anticipatory actions (i.e., actions in preparation for a potential upcoming conflict) have been found to be more prevalent among experienced drivers in a driving simulator study where driving was the sole task. The influence of secondary tasks on anticipatory driving has not yet been investigated, despite the prevalence and negative effects of distraction widely documented in the literature. A driving simulator experiment was conducted with 16 experienced and 16 novice drivers to address this gap with half of the participants provided with a self-paced visual-manual secondary task. More anticipatory actions were observed among experienced drivers in general compared to novices; experienced drivers also exhibited more efficient visual scanning behaviors. Secondary task engagement reduced anticipatory actions for both experienced and novice drivers.

Consistency between subjectively and objectively measured hazard perception skills among young male drivers

Young male drivers have lower hazard perception skills (HPS) than older and more experienced drivers and a tendency to overestimate their skills in hazardous situations. Both factors contribute to an over-representation in traffic accidents. Based on a sample of 63 drivers aged 18-24, this study compares the consistency of HPS measured by objective and subjective measures and the link between these measures is the key contribution of the study. Both visible and hidden hazards are included. Objective measures of HPS include responsiveness and eye movements while driving in a driving simulator. Subjective measures of HPS include self-reports derived based on the Hazard Perception Questionnaire (HPQ), Driving Skill Questionnaire (DSQ), and Brief Sensation Seeking Scale (BSSS). Results show that drivers who respond to the hazards on time, as compared to drivers who do not respond, have higher scores on subjective measures of HPS and higher driving skills in the visible but not in the hidden condition. Eye movement analysis confirms the difference and shows that response in time to hazards indicate higher HPS and young drivers are poor at detecting hidden hazards. Drivers with a response in time locate the hazard faster, have more fixations, but dwell less on the hazard. At the same time, those who do not respond have a later first fixation and fewer but longer fixations on the hazard. High sensation seeking drivers respond to visible hazards on time, suggesting that sensation seeking does not affect HPS negatively when the hazard is visible. To enhance the HPS among young drivers, the results of this study suggest that specific hazard perception training is relevant, especially for hazards that require more advanced HPS.

How much time do drivers need to obtain situation awareness? A laboratory-based study of automated driving

Drivers of automated cars may occasionally need to take back manual control after a period of inattentiveness. At present, it is unknown how long it takes to build up situation awareness of a traffic situation. In this study, 34 participants were presented with animated video clips of traffic situations on a three-lane road, from an egocentric viewpoint on a monitor equipped with eye tracker. Each participant viewed 24 videos of different durations (1, 3, 7, 9, 12, or 20 s). After each video, participants reproduced the end of the video by placing cars in a top-down view, and indicated the relative speeds of the placed cars with respect to the ego-vehicle. Results showed that the longer the video length, the lower the absolute error of the number of placed cars, the lower the total distance error between the placed cars and actual cars, and the lower the geometric difference between the placed cars and the actual cars. These effects appeared to be saturated at video lengths of 7-12 s. The total speed error between placed and actual cars also reduced with video length, but showed no saturation up to 20 s. Glance frequencies to the mirrors decreased with observation time, which is consistent with the notion that participants first estimated the spatial pattern of cars after which they directed their attention to individual cars. In conclusion, observers are able to reproduce the layout of a situation quickly, but the assessment of relative speeds takes 20 s or more.

Game-based situation awareness training for child and adult cyclists

Safe cycling requires situation awareness (SA), which is the basis for recognizing and anticipating hazards. Children have poorer SA than adults, which may put them at risk. This study investigates whether cyclists' SA can be trained with a video-based learning game. The effect of executive working memory on SA was also studied. Thirty-six children (9-10 years) and 22 adults (21-48 years) played the game. The game had 30 video clips filmed from a cyclist's perspective. Each clip was suddenly masked and two or three locations were presented. The player's task was to choose locations with a potential hazard and feedback was given for their answers. Working memory capacity (WMC) was tested with a counting span task. Children's and adults' performance improved while playing the game, which suggests that playing the game trains SA. Adults performed better than children, and they also glanced at hazards more while the video was playing. Children expectedly had a lower WMC than adults, but WMC did not predict performance within the groups. This indicates that SA does not depend on WMC when passively viewing videos.

Hazard Perception in Driving

Hazard perception in driving refers to a driver’s ability to anticipate potentially dangerous situations on the road ahead and has been the subject of research for over 50 years. It is typically measured using computer-based hazard-perception tests and has been associated with both retrospective and prospective crash risk, as well as key crash-risk factors such as distraction, fatigue, alcohol consumption, speed choice, and age-related declines. It can also differentiate high- and lower-risk driver groups. The problem is that it is also a skill that appears to take decades of driving experience to acquire. This raises the question of whether it is possible and practical to accelerate this learning process via assessment and training in order to improve traffic safety. We have evidence that, in contrast to most driver education and assessment interventions, hazard-perception testing and training appear to have the capability to reduce crash risk. For example, the inclusion of a hazard-perception test in the UK driver licensing process has been estimated to reduce drivers’ non-low-speed public-road crash rates by 11.3% in the year following their test.