Search

• This study constructs a prediction model of driver's takeover time based on individual characteristics, external environment, and situation awareness variables. The performance of the BM + SA model (with situation awareness variables) was better than that of the BM model (without situation awareness variables). This paper has proved that situation awareness is important to takeover time, and the driver's situation awareness should be considered in the study of takeover time. This study can provide support for predicting driver's takeover time. • This study analyzes the main effect of input variables (individual characteristics, external environment, and situation awareness variables) on takeover time and the interactive contribution made by the variables. This study can support analyzing the influence mechanism on takeover time. • This study introduces the Shapely value to explain the XGBoost model, and analyze the contribution of each input variable and their interactive contribution. In addition, the Shapely value explains the variation of individual prediction results. This supports analyzing the contribution of various factors in individual prediction results. The driver's takeover time is crucial to ensure a safe takeover transition in conditional automated driving. The study aimed to construct a prediction model of driver's takeover time based on individual characteristics, external environment, and situation awareness variables. A total of 18 takeover events were designed with scenarios, non-driving-related tasks, takeover request time, and traffic flow as variables. High-fidelity driving simulation experiments were carried out, through which the driver's takeover data was obtained. Fifteen basic factors and three dynamic factors were extracted from individual characteristics, external environment, and situation awareness. In this experiment, these 18 factors were selected as input variables, and XGBoost and Shapely were used as prediction methods. A takeover time prediction model (BM + SA model) was then constructed. Moreover, we analyzed the main effect of input variables on takeover time, and the interactive contribution made by the variables. And in this experiment, the 15 basic factors were selected as input variables, and the basic takeover time prediction model (BM model) was constructed. In addition, this study compared the performance of the two models and analyzed the contribution of input variables to takeover time. The results showed that the goodness of fit of the BM + SA model (Adjusted_ R 2) was 0.7746. The XGBoost model performs better than other models (support vector machine, random forest, CatBoost, and LightBoost models). The relative importance degree of situation awareness variables, individual characteristic variables, and external environment variables to takeover time gradually reduced. Takeover time increased with the scan and gaze durations and decreased with pupil area and self-reported situation awareness scores. There was also an interaction effect between the variables to affect takeover time. Overall, the performance of the BM + SA model was better than that of the BM model. This study can provide support for predicting driver's takeover time and analyzing the mechanism of influence on takeover time. This study can provide support for the development of real-time driver's takeover ability prediction systems and optimization of human–machine interaction design in automated vehicles, as well as for the management department to evaluate and improve the driver's takeover performance in a targeted manner. [ABSTRACT FROM AUTHOR]

• The present study uses a PCM-based approach to assess AV operator SA over an extended fatiguing automated drive. • Operator SA is assessed at two critical takeover events near the beginning and end of the simulated drive. • Operator SA is shown to decline in response to passive monitoring of the simulated AV. • Self-selected NDRT engagement counteracts SA decline. • Impaired schema-related SA appears to explain poorer outcomes in the AV monitoring condition compared to the NDRT-permitted condition. Vehicle automation promises to reduce the demands of the driving task, making driving less fatiguing, more convenient, and safer. Nevertheless, Level 3 automated vehicles rely on a human driver to be ready to resume control, requiring the driver to reconstruct situation awareness (SA) and resume the driving task. Understanding the interaction between non-driving-related task (NDRT) use, SA, and takeover capacity is important because an effective takeover is entirely dependent on, and scaffolds from, effectively reconstructed SA. While a number of studies have looked at the behavioural impact of being 'in- or on-the-loop', fewer consider the cognitive impact, particularly the consequences for SA. The present study exposed participants to an extended simulated automated drive involving two critical takeover scenarios (early- and late-drive). We compared automated vehicle (AV) operators who were required to passively monitor the vehicle to those engaging with self-selected NDRTs. Monitoring operators demonstrated lower total- and schema-specific SA count scores following a fatiguing drive compared to those engaging with self-selected NDRTs. NDRT engagement resulted in no significant difference in SA count scores early- and late-drive. Assessment of differences in the type and sensory modality of NDRTs indicated operators make fundamentally different selections about the NDRTs they engage with in an automated driving environment compared to a manual environment. The present study provides further evidence linking SA and AV operator behaviour and underscores the need to understand the role of SA in takeover capacity. Our findings suggest that although SA declines over time regardless of driving task requirements (Monitoring versus NDRT engagement), NDRT use may facilitate better SA construction, with implications for the regulation of NDRT use in AVs as the technology progresses. [ABSTRACT FROM AUTHOR]

Highlights • Multiple methods were used to demonstrate the validity of a hazard perception test. • Scores yielded experience-level differences and correlated with an existing measure. • Crucially, scores predicted the frequency of heavy-braking during real driving. • Heavy-braking events had been measured using low-cost consumer-level dashcams. • Such devices are therefore a viable means of measuring real-world driving behaviour. Abstract Computer-based hazard perception tests are used in a number of countries as part of the driver licensing processes, and hence evaluating the validity of such tests is crucial. One strategy for assessing the validity of the scores generated by a hazard perception test is to determine whether they can predict on-road driving performance. Only a few prior studies have attempted this, all relying on the subjective ratings of an examiner who was present during a single brief drive and was not blind to the driver's demographic characteristics, potentially contaminating the outcomes. Additionally, only one such study focused on the most relevant participant group with respect to the validity of tests used in licencing processes, namely young drivers. We sought to remedy this situation in the present project by measuring young drivers' performance over an extended period of everyday driving via g-force triggered video cameras ("dashcams") installed in their own vehicles. As a precursor to the dashcam study itself, we developed a new computerized hazard perception test and assessed the validity of its scores by more traditional means (Study 1). As expected, test scores distinguished between high-risk and lower-risk driver groups, and correlated with scores on an established hazard perception test previously shown to predict crash risk. In the subsequent dashcam study (Study 2), the frequency of heavy-braking events (controlling for distance driven) was used as a more objective measure of driving performance. Results indicated that drivers with higher rates of heavy braking had slower hazard perception response times, further supporting the use of these scores as a valid measure of drivers' ability to exercise hazard perception skill during real driving. More generally, this study also demonstrates the viability of using low-cost off-the-shelf dashcams to measure real-world driving behaviour. [ABSTRACT FROM AUTHOR]

Introduction Even though child bicyclists are highly vulnerable in traffic only few studies focused on providing child bicyclists with means to enhance their abilities to deal with the complexity of dynamic traffic situations. The current study therefore evaluated whether a brief hazard perception intervention might be effective to improve hazard perception skills in child bicyclists towards a level more comparable to adult bicyclists. Methods Eighty children of the fourth grade (9.03 ± 0.43 years; 34 girls) and forty-six adults (34.67 ± 14.25 years age; 24 woman) first performed a Hazard Perception test for bicyclists. Response rate, reaction times, first fixation, duration of the first fixation, dwell time and total number of fixations on the events were measured. Next, the children took part in the HP intervention in which video clips of dangerous traffic situations were presented. The intervention comprised two classroom sessions of one hour (1/week). A post-test was performed one day after and the retention-test three weeks after the intervention. Results Children responded to more covert hazards immediately after the intervention (p < 0.05), but did not improve their response rate for overt hazards. Reaction times for the covert hazards improved on the post-test (p < 0.001) compared to the pre-test but this effect was reduced on the retention test. There was no effect of the intervention for entry time of the first fixation but the duration of the first fixation increased for the covert hazards (p < 0.05). Children made fewer fixations on the event compared to adults (p < 0.001), except for the covert hazards on the retention-test. The training also increased the number of fixations for the overt hazards on the post-test (p < 0.001) and the retention-test (p < 0.001) but only increased on the retention test for the covert hazards (p < 0.001). Conclusion The results demonstrated that a brief intervention for training hazard perception skills in child bicyclists is able to improve children’s situation awareness and hazard perception for potential dangerous situations. The training, however, was too short to improve children to higher adult levels. [ABSTRACT FROM AUTHOR]

This driving simulator study, conducted as part of the EU AdaptIVe project, investigated drivers’ performance in critical traffic events, during the resumption of control from an automated driving system. Prior to the critical events, using a between-participant design, 75 drivers were exposed to various screen manipulations that varied the amount of available visual information from the road environment and automation state, which aimed to take them progressively further ‘out-of-the-loop’ (OoTL). The current paper presents an analysis of the timing, type, and rate of drivers’ collision avoidance response, also investigating how these were influenced by the criticality of the unfolding situation. Results showed that the amount of visual information available to drivers during automation impacted on how quickly they resumed manual control, with less information associated with slower take-over times, however, this did not influence the timing of when drivers began a collision avoidance manoeuvre. Instead, the observed behaviour is in line with recent accounts emphasising the role of scenario kinematics in the timing of driver avoidance response. When considering collision incidents in particular, avoidance manoeuvres were initiated when the situation criticality exceeded an Inverse Time To Collision value of ≈0.3 s −1 . Our results suggest that take-over time and timing and quality of avoidance response appear to be largely independent, and while long take-over time did not predict collision outcome, kinematically late initiation of avoidance did. Hence, system design should focus on achieving kinematically early avoidance initiation, rather than short take-over times. [ABSTRACT FROM AUTHOR]

Efficient processing of visual information is crucial to safe driving. Previous research has demonstrated that driving experience strongly affects attentional allocation, with large differences between novice and experienced drivers. Expanding on this, we explored the influence of non-driving experiences on attentional allocation by comparing drivers with and without cycling experience. Based on situation awareness field studies, we predicted cyclist-drivers would demonstrate superior performance. Participants were 42 experienced drivers (17 female, 25 male) aged 30–50 years ( M = 39.8): 20 drivers and 22 cyclist-drivers. The experiment used a change detection flicker task, in which participants must determine whether two alternating images are identical (change-absent) or differ in a single detail (change-present). The changed object was either a road sign, car, pedestrian, or bicycle. Change target significantly affected both accuracy and response time: all participants were slower and less accurate at detecting changes to road signs, compared with when the change was a moving road user (i.e., car, pedestrian, bicycle). Accuracy did not differ significantly between groups, but cyclist-drivers were significantly faster than drivers at identifying changes, with the effect being largest for bicycle and sign changes. The results suggest that cycling experience is associated with more efficient attentional processing for road scenes. [ABSTRACT FROM AUTHOR]

Child bicyclists are at greater risk to get involved in a traffic accident. Although hazard perception tests between inexperienced and experienced car drivers revealed significant differences in perceptual-cognitive skills, a similar test for bicyclists is not yet existent. Therefore this study aimed to compare visual search patterns and reaction times of child bicyclists and adult bicyclists utilizing a hazard perception test for cyclists. Seventy-five children and forty-one adults were presented with eleven video clips filmed from the perspective of the bicyclist. The participants were required to press a response button whenever they detected a hazardous situation. Children were found to have significantly delayed reaction times and time until the first fixation on the latent covert hazards compared to adults. The inefficient visual search patterns in children may be attributed to an immature visual system. However, the finding that children fixated later on the hazards and only responded to the covert latent hazards when they became salient indicate difficulties with identifying possible hazards. Altogether, the findings of this study suggest that children’s situation awareness is dependent upon experience too, and not just maturation. Therefore, implications for training young bicyclists will be discussed. [ABSTRACT FROM AUTHOR]

Encouraging more children to bicycle would produce both environmental and health benefits, but bicycling accidents are a major source of injuries and fatalities among children. One reason for this may be children’s less developed hazard perception skills. We assume that children’s situation awareness could be trained with a computer based learning game, which should also improve their hazard perception skills. In this paper, we present a prototype for such a game and pilot it with 8–9 year old children. The game consisted of videos filmed from a bicyclist’s perspective. Using a touchscreen, the player's task was to point out targets early enough to gain points. The targets were either overt (other visible road users on a potentially conflicting course) or covert (occlusions, i.e. locations where other road users could suddenly emerge). If a target was missed or identified too late, the video was paused and feedback was given. The game was tested with 49 children from the 2nd grade of primary school (aged 8–9). 31 young adults (aged 22–34) played the game for comparison. The effect of the game on situation awareness was assessed with situation awareness tests in a crossover design. Similar videos were used in the tests as in the game, but instead of pointing out the targets while watching, the video was suddenly masked and participants were asked to locate all targets which had been present just before the masking, choosing among several possible locations. Their performance was analyzed using Signal Detection Theory and answer latencies. The game decreased answer latency and marginally changed response bias in a less conservative direction for both children and adults, but it did not significantly increase sensitivity for targets. Adults performed better in the tests and in the game, and it was possible to satisfactorily predict group membership based on the scores. Children found it especially difficult to find covert targets. Overall, the described version of the learning game cannot be regarded as an effective tool for situation awareness/hazard perception training, but ways to improve the game are discussed. [ABSTRACT FROM AUTHOR]

Drivers’ hazard perception ability has been found to predict crash risk, and novice drivers appear to be particularly poor at this skill. This competency appears to develop only slowly with experience, and this could partially be a result of poor quality performance feedback. We report an experiment in which we provided high-quality artificial feedback on individual drivers’ performance in a validated video-based hazard perception test via either: (1) a graph-based comparison of hazard perception response times between the test-taker, the average driver, and an expert driver; (2) a video-based comparison between the same groups; or (3) both. All three types of feedback resulted in both an improvement in hazard perception performance and a reduction in self-rated hazard perception skill, compared with a no-feedback control group. Video-based and graph-based feedback combined resulted in a greater improvement in hazard perception performance than either of the individual components, which did not differ from one another. All three types of feedback eliminated participants’ self-enhancement bias for hazard perception skill. Participants judged both interventions involving video feedback to be significantly more likely to improve their real-world driving than the no feedback control group. While all three forms of feedback had some value, the combined video and graph feedback intervention appeared to be the most effective across all outcome measures. [ABSTRACT FROM AUTHOR]

The current study aims to obtain knowledge about the nature of the processes involved in Hazard Perception, using measurement techniques to separate and independently quantify these suspected sub-processes: Sensation, Situation Awareness (recognition, location and projection) and decision-making. It applies Signal Detection Theory analysis to Hazard Perception and Prediction Tasks. To enable the calculation of Signal Detection Theory parameters, video-recorded hazardous vs. quasi-hazardous situations were presented to the participants. In the hazardous situations it is necessary to perform an evasive action, for instance, braking or swerving abruptly, while the quasi-hazardous situations do not require the driver to make any evasive manoeuvre, merely to carry on driving at the same speed and following the same trajectory. A first Multiple Choice Hazard Perception and Prediction test was created to measure participants’ performance in a What Happens Next? Task. The sample comprised 143 participants, 47 females and 94 males. Groups of non-offender drivers (learner, novice and experienced) and offender drivers (novice and experienced) were recruited. The Multiple Choice Hazard Perception and Prediction test succeeded in finding differences between drivers according to their driving experience. In fact, differences exist with regard to the level of hazard discrimination (d′ prime) by drivers with different experience (learner, novice and experienced drivers) and profile (offenders and non-offenders) and these differences emerge from Signal Detection Theory analysis. In addition, it was found that experienced drivers show higher Situation Awareness than learner or novice drivers. On the other hand, although offenders do worse than non-offenders on the hazard identification question, they do just as well when their Situation Awareness is probed (in fact, they are as aware as non-offenders of what the obstacles on the road are, where they are and what will happen next). Nevertheless, when considering the answers participants provided about their degree of cautiousness, experienced drivers were more cautious than novice drivers, and non-offender drivers were more cautious than offender drivers. That is, a greater number of experienced and non-offender drivers chose the answer “I would make an evasive manoeuvre such as braking gradually”. [ABSTRACT FROM AUTHOR]

Complex socio-technical systems, such as road tunnels, can be designed and developed with more or less elements that can either positively or negatively affect the capability of their agents to recognise imminent threats or vulnerabilities that possibly lead to accidents. This capability is called risk Situation Awareness (SA) provision. Having as a motive the introduction of better tools for designing and developing systems that are self-aware of their vulnerabilities and react to prevent accidents and losses, this paper introduces the Risk Situation Awareness Provision (RiskSOAP) methodology to the field of road tunnel safety, as a means to measure this capability in this kind of systems. The main objective is to test the soundness and the applicability of RiskSOAP to infrastructure, which is advanced in terms of technology, human integration, and minimum number of safety requirements imposed by international bodies. RiskSOAP is applied to a specific road tunnel in Greece and the accompanying indicator is calculated twice, once for the tunnel design as defined by updated European safety standards and once for the ‘as-is’ tunnel composition, which complies with the necessary safety requirements, but calls for enhancing safety according to what EU and PIARC further suggest. The derived values indicate the extent to which each tunnel version is capable of comprehending its threats and vulnerabilities based on its elements. The former tunnel version seems to be more enhanced both in terms of it risk awareness capability and safety as well. Another interesting finding is that despite the advanced tunnel safety specifications, there is still room for enriching the safe design and maintenance of the road tunnel. [ABSTRACT FROM AUTHOR]

In 2008, the state of Queensland in Australia introduced a video-based hazard perception test as part of the licensing process for new drivers. A key validity check for such a test is whether scores are associated with crash involvement. We present data demonstrating that drivers who failed the hazard perception test (based on a ROC curve-derived pass mark) were 25% [95% confidence interval (CI) 6%, 48%] more likely to be involved in an active crash (defined as a crash occurring while the driver’s vehicle was moving but they were not engaged in parking or reversing) during a one year period following the test (controlling for driving exposure, age, and sex). Failing drivers were also 17% (95% CI 6%, 29%) more likely to have been involved in active crashes prior to the test, in the period since obtaining their provisional license. These data support the proposal that the hazard perception test is a valid measure of crash-related driving performance. [ABSTRACT FROM AUTHOR]

• The study investigates how takeover request (ToR) lead time is associated with driver situation awareness (SA), takeover reaction time, and subjective evaluations in freeway exiting takeovers in Level 3 AVs. • The positive effect of a longer ToR lead time on driver SA saturates at 16–30 s. • The average driver took over control of AVs at the last moment before exiting in 6 s and 8 s ToR conditions but did not use the "last-moment takeover" strategy when there was longer than 8 s. Conditional automation systems allow drivers to turn their attention away from the driving task in certain scenarios but still require drivers to gain situation awareness (SA) upon a takeover request (ToR) and resume manual control when the system is unable to handle the upcoming situation. Unlike time-critical takeover situations in which drivers must respond within a relatively short time frame, the ToRs for non-critical events such as exiting from a freeway can be scheduled way ahead of time. It is unknown how the ToR lead time affects driver SA for resuming manual control and when to send the ToR is most appropriate in non-critical takeover events. The present study conducted a web-based, supervised experiment with 31 participants using conditional automation systems in freeway existing scenarios while playing a mobile game. Each participant experienced 12 trials with different ToR lead times (6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 45, and 60 s) for exiting from freeways in a randomized order. Driver SA was measured by using a freeze probe technique in each trial when the participant pressed the spacebar on the laptop to simulate the takeover action. Results revealed a positive effect of longer ToR lead times on driver SA for resuming control to exit from freeways and the effect leveled off at the lead time of 16–30 s. The participants tended to postpone their takeover actions further when they were given a longer ToR lead time and it did not level off up to 60 s. Nevertheless, not all drivers waited till the last moment to take over AVs even though they did not get sufficient SA. The ToR lead time of 16–30 s was recommended for better SA; and it could be narrowed down to 25–30 s if considering the subjective evaluations on takeover readiness, workload, and trust. The findings provide implications for the future design of conditional automation systems used for freeway driving. [ABSTRACT FROM AUTHOR]

Phone use while driving has become one of the priority issues in road safety, given that it may lead to decreased situation awareness and deteriorated driving performance. It has been suggested that drivers can regulate their exposure to secondary tasks and seek for compatibility of phone use and driving. Phone use strategies include the choice of driving situations with low demands and interruptions of the interaction when the context changes. Traffic light situations at urban intersections imply both a temptation to use the phone while waiting at the red traffic light and a potential threat due to the incompatibility of phone use and driving when the traffic light turns green. These two situations were targeted in a roadside observation study, with the aim to investigate the existence of a phone use strategy at the red traffic light and to test its effectiveness. N = 124 phone users and a corresponding control group of non-users were observed. Strategic phone use behaviour was detected for visual–manual interactions, which are more likely to be initiated at the red traffic light and tend to be stopped before the vehicle moves off, while calls are less likely to be limited to the red traffic light situation. As an indicator of impaired situation awareness, delayed start was associated to phone use and in particular to visual–manual interactions, whether phone use was interrupted before moving off or not. Traffic light situations do not seem to allow effective application of phone use strategies, although drivers attempt to do so for the most demanding phone use mode. The underlying factors of phone use need to be studied so as to reduce the temptation of phone use and facilitate exposure regulation strategies. [ABSTRACT FROM AUTHOR]

In 2008 a runaway chemical reaction caused an explosion at a methomyl unit in West Virginia, USA, killing two employees, injuring eight people, evacuating more than 40,000 residents adjacent to the facility, disrupting traffic on a nearby highway and causing significant business loss and interruption. Although the accident was formally investigated, the role of the situation awareness (SA) factor, i.e., a correct understanding of the situation, and appropriate models to maintain SA, remain unexplained. This paper extracts details of abnormal situations within the methomyl unit and models them into a situational network using dynamic Bayesian networks. A fuzzy logic system is used to resemble the operator’s thinking when confronted with these abnormal situations. The combined situational network and fuzzy logic system make it possible for the operator to assess such situations dynamically to achieve accurate SA. The findings show that the proposed structure provides a useful graphical model that facilitates the inclusion of prior background knowledge and the updating of this knowledge when new information is available from monitoring systems. [ABSTRACT FROM AUTHOR]

Abstract: Crashes between cars and trains at rail level crossings are problematic worldwide. Despite this, key facets of driver behaviour at rail level crossings, such as situation awareness and decision making, remain ambiguous. This is largely down to the inability of existing methodologies to describe or evaluate the cognitive aspects of driver behaviour when negotiating rail level crossings. This paper showcases an on-road approach for examining driver situation awareness at rail level crossings. The study presented involved participants, classified either as novice or experienced drivers, providing concurrent verbal protocols as they drove a pre-determined urban route incorporating four rail level crossings. Driver situation awareness was modelled using a network analysis-based approach and the structure and content of the networks was assessed. The analysis revealed key differences between novice and experienced drivers situation awareness at rail level crossings. In closing, the benefits of the on-road approach are discussed and a series of wider driver behaviour applications are proposed. [Copyright &y& Elsevier]

Highlights: [•] Injuries to pedestrians using mobile phones increased in numbers and as a percentage of total pedestrian injuries from 2004 to 2010. [•] For cell-phone related injuries, the increase for pedestrians parallel that for drivers. [•] Pedestrian injuries related to mobile phone use were higher for men than women. [•] Pedestrian injuries related to mobile phone use were higher for young people. [•] Walking and talking or texting can be dangerous. [ABSTRACT FROM AUTHOR]

• The present study frames expert and non-expert drivers' situation awareness (SA) within the Perceptual Cycle Model. • SA is assessed along with driver gaze behaviour to correlate behavioural and verbal report measures. • Both verbal counts and fixation-related gaze are found to reliably differentiate expert and non-expert drivers. • Differences in expert and non-expert gaze behaviour informs an understanding of expert SA. 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. [ABSTRACT FROM AUTHOR]

• Learner drivers completed a 6-week online hazard perception training course. • Parents supervised the online training and real-world transfer exercises. • Both learners and parents had improved hazard perception skill after training. • Learners demonstrated safer following distance preferences after training. • All learners and parents who completed the course reported safer real driving. We previously found that a six-session online hazard perception training course, which incorporates evidence-based learning strategies and footage of over a hundred real crashes, improved hazard perception skill and reduced risk-taking intentions in novice drivers who had passed their on-road driving test within the previous three years. However, one issue with targeting crash-prevention training at individuals who are already driving unsupervised is that drivers are at their highest crash risk immediately after they pass their on-road driving test. That is, the training may arrive too late to protect drivers while they are at their most vulnerable. It is also possible that it may prove difficult to persuade drivers to complete an unsupervised training course if they are already licensed to drive independently. Given that learner drivers cannot drive unsupervised, and that they are typically supervised by a parent, one potential strategy is to target the training at learners and to ask their parents to provide one-on-one mentoring throughout the course. We therefore recruited learner driver/parent-supervisor dyads to participate in a randomized control study, with the objective of examining the effects of the hazard perception training course on aspects of driving behaviour associated with crash risk (as measured using validated computer-based tests). Outcome measures included two hazard perception skill assessments (a response time hazard perception test and a verbal response hazard prediction test), and three tests assessing aspects of risk-taking propensity in driving (speed choice, following distance, and gap acceptance). Learners who completed the course (N = 26) significantly improved their scores on both hazard perception skill measures, and also chose safer following distances, compared with a waitlist control group (N = 23). However, the training did not significantly reduce learners' speed choice or gap acceptance propensity. The hazard perception skill of parent-supervisors, who observed the course but did not complete it, also improved on both hazard perception measures, relative to controls. Additionally, both learners and their parent-supervisors reported a range of positive effects on the learners' real-world driving performance. These results suggest that this type of hazard perception training could be beneficial if deployed during the learner phase of driver licensing. [ABSTRACT FROM AUTHOR]

Abstract: This research investigates risk awareness abilities among different populations of motorcyclists. Risk awareness is defined here as an extension of the Situational Awareness theory applied to critical driving situations. This study is more particularly focused on two main cognitive abilities supporting risk awareness: hazard detection, corresponding to riders’ skill to perceive critical event occurring in the road environment and to identify it as a threat, and situational criticality assessment, corresponding to a subjective assessment of the accident risk. From this theoretical framework, the aim is to compare motorcyclists’ performances in risk awareness according to their experience in motorcycling. Four populations of motorcyclists are investigated: Professional (Policemen), Experienced riders, Novices, and Beginners. Method implemented is based of a set of 25 video sequences of driving situations presenting a risk of collision. Participants’ task was firstly to stop the video film if they detect a hazard. Then, at the end of each sequence, they have also to assess the criticality of the driving situation as a whole, with a Likert scale (from 0 to 100% of criticality). Results obtained show that cognitive abilities in both (i) hazard detection and (ii) situational criticality assessment depend of the riding experience, and are learnt from two different timing. On one side, Professional and Experienced riders obtained better results than Novices and Beginners for hazard perception (i.e. shortest reaction time). In terms of situational criticality assessment, Beginners underestimate the situational risk and seem overconfident in their abilities to manage the situational risk, against Novices, Professional and Experienced riders, who have better competences in criticality assessment. From these empirical results, a conceptual model of motorcyclists’ Risk Awareness is proposed. [Copyright &y& Elsevier]

Abstract: Studies from neurophysiology and neuropsychology provide support for two separate object- and location-based visual systems, ventral and dorsal. In the driving context, a study was conducted using a change detection paradigm to explore drivers’ ability to monitor the dynamic traffic flow, and the effects of visual disruption on these two visual systems. While driving, a discrete change, such as vehicle location, color, or identity, was occasionally made in one of the vehicles on the road ahead of the driver. Experiment results show that without visual disruption, all changes were detected very well; yet, these equally perceivable changes were disrupted differently by a brief blank display (150ms): the detection of location changes was especially reduced. The disruption effects were also bigger for the parked vehicle compared to the moving ones. The findings support the different roles for two visual systems in monitoring the dynamic traffic: the “where”, dorsal system, tracks vehicle spatiotemporal information on perceptual level, encoding information in a coarse and transient manner; whereas the “what”, ventral system, monitors vehicles’ featural information, encoding information more accurately and robustly. Both systems work together contributing to the driver''s situation awareness of traffic. Benefits and limitations of using the driving simulation are also discussed. [Copyright &y& Elsevier]

• In conditionally automated vehicles, drivers may engage in non-driving-related tasks (NDRTs). • Engagement in NDRTs may limit drivers' situation awareness (SA) when takeover is needed. • Eye-tracking was used in a driving simulator study to understand the effects of visual engagement in NDRTs on SA. • Longer times spent viewing the driving scene, and more dispersed visual attention allocation, resulted in better overall SA. • Results can inform the development of real-time SA assessment techniques using eye movements. Automated driving systems are becoming increasingly prevalent throughout society. In conditionally automated vehicles, drivers may engage in non-driving-related tasks (NDRTs), which can negatively affect their situation awareness (SA) and preparedness to resume control of the vehicle, when necessary. Previous work has investigated engagement in NDRTs, but questions remain unanswered regarding its effect on drivers' SA during a takeover event. The objective of the current study is to use eye-tracking to aid in understanding how visual engagement in NDRTs affects changes in SA of the driving environment after a takeover request (TOR) has been issued. Thirty participants rode in a simulated SAE Level 3 automated driving environment and engaged in three separate pre-TOR tasks (Surrogate Reference Task, Monitoring Task, and Peripheral Detection Task) until presented with a TOR. Situation Awareness Global Assessment Technique (SAGAT) scores and gaze behavior were recorded during the post-TOR segment. Overall, longer times spent viewing the driving scene, and more dispersed visual attention allocation, were observed to be associated with better overall SA. Also, location-based eye tracking metrics show most promise in differentiating between task conditions with significantly different SAGAT scores. Findings from this work can inform the development of real-time SA assessment techniques using eye movements and ultimately contribute to improved operator roadway awareness for next-generation automated transportation. [ABSTRACT FROM AUTHOR]

Abstract: Driver distraction is a major cause of traffic accidents, with mobile telephones as a key source of distraction. In two studies, we examined distraction of pedestrians associated with mobile phone use. The first had 60 participants walk along a prescribed route, with half of them conversing on a mobile phone, and the other half holding the phone awaiting a potential call, which never came. Comparison of the performance of the groups in recalling objects planted along the route revealed that pedestrians conversing recalled fewer objects than did those not conversing. The second study had three observers record pedestrian behavior of mobile phone users, i-pod users, and pedestrians with neither one at three crosswalks. Mobile phone users crossed unsafely into oncoming traffic significantly more than did either of the other groups. For pedestrians as with drivers, cognitive distraction from mobile phone use reduces situation awareness, increases unsafe behavior, putting pedestrians at greater risk for accidents, and crime victimization. [Copyright &y& Elsevier]

This study focused on how teams allocated attention between a driving-related spatial task and a verbal task, and how different kinds of verbal interactions affected performance of the driving-related task. In Experiment 1, 29 two-person teams performed an interactive verbal task while one team member also performed a simulated driving task. Of the team members performing only the verbal task, half could see their partner’s spatial situation, as a car passenger can (in-person condition), and half were remotely located, similar to someone speaking to a driver using a cell-phone. Teams interacted verbally at an overall slower rate during remote than in-person interactions, suggesting that remote verbal interactions are more difficult than in-person interactions. Verbal interactions degraded situation awareness for driving-related information while performing the spatial task; and this degradation was not greater during remote than in-person interactions. Experiment 2 used a faster-paced verbal task and found greater degradation of situation awareness due to the verbal task. These findings are potentially relevant to the issue of how passenger and cell-phone conversations affect driving performance. [Copyright &y& Elsevier]

• We created a 6-week video-based online hazard perception training course for drivers. • The course incorporated evidence-based training methods and >100 real crash videos. • Trainees' scores improved on validated hazard perception and hazard prediction tests. • The course led to safer vehicle following distance preferences in a video-based test. • All trainees reported improvements in their on-road driving safety after training. A key goal of driver training is to teach drivers to avoid crashes. However, in traditional driver training, drivers are unlikely to see even a single example of the class of event that we want them to learn to avoid. We developed a six-session automated online hazard perception training course for drivers, which incorporates a range of evidence-based strategies and employs extensive video footage of real crashes. We evaluated this course in a randomized control trial by examining its effects on previously-validated computer-based measures of hazard perception, hazard prediction, speed choice, following distance, and gap acceptance propensity, as well as self-rated measures of driver skill, safety, and real world transfer. We found that the course resulted in significant improvements in hazard perception response time and hazard prediction scores, and significantly longer vehicle following distances. Additionally, all participants in the trained group reported that their real world driving behaviour had improved. No significant training effects were found for the other measures. The results suggest that the course can improve key behaviours associated with crash risk. [ABSTRACT FROM AUTHOR]

• Limited situation awareness(SA) may cause accidents while operating a mobile plant. • Mobile plant operator's SA of other people in proximity is investigated. • Forklift operator's SA about other workers is affected by the complexity of the subtasks. • Control measures are proposed to prevent struck-by or caught in/between accidents. Forklifts are among the machines involved with the highest levels of occupational fatalities. As many accidents involved with a forklift can be attributed to the low situation awareness (SA) of the operator, it is essential to understand the factors influencing a forklift operator's SA for reducing forklift accidents, especially of collision type. Against this background, this research aims to investigate how a forklift operator's SA about other people around can be influenced by the type of subtasks they are carrying out. In this research, a virtual reality (VR) environment is used as the experiment environment, in which subjects perform a series of subtasks, such as driving, turning, reversing, loading and unloading, with a VR forklift simulation model. A SAGAT—an established SA measurement technique based on a series of queries targeting Level 1, 2, and 3 SA—is used as the main method to collect data about subjects' SA in the experiment. The analysis of the data reveals that a forklift operator is likely to have a reduced SA about the workers around when he/she is performing a loading or unloading task due to attention narrowing, which occurs when a person concentrates on a cognitively demanding task. The findings provide insights into how forklift operator SA could be improved through an SA-oriented safety training program and also how sensing technologies might assist forklift operators with maintaining a good SA. [ABSTRACT FROM AUTHOR]