Real-time driver identification in IoV: A deep learning and cloud integration approach

The Internet of Vehicles (IoV) emerges as a pivotal extension of the Internet of Things (IoT), specifically geared towards transforming the automotive landscape. In this evolving ecosystem, the demand for a seamless end-to-end system becomes paramount for enhancing operational efficiency and safety. Hence, this study introduces an innovative method for real-time driver identification by integrating cloud computing with deep learning. Utilizing the integrated capabilities of Google Cloud, Thingsboard, and Apache Kafka, the developed solution tailored for IoV technology is adept at managing real-time data collection, processing, prediction, and visualization, with resilience against sensor data anomalies. Also, this research suggests an appropriate method for driver identification by utilizing a combination of Convolutional Neural Networks (CNN) and multi-head self-attention in the proposed approach. The proposed model is validated on two datasets: Security and collected. Moreover, the results show that the proposed model surpassed the previous works by achieving an accuracy and F1 score of 99.95%. Even when challenged with data anomalies, this model maintains a high accuracy of 96.2%. By achieving accurate driver identification results, the proposed end-to-end IoV system can aid in optimizing fleet management, vehicle security, personalized driving experiences, insurance, and risk assessment. This emphasizes its potential for road safety and managing transportation more effectively.

"It is a different type of policing than in the bush": Police officers' perceptions of the differences in enforcement of the phone use while driving legislation in rural and urban areas

Mobile phone use while driving continues to be a significant road safety concern, despite the severe legal countermeasures to reduce this behaviour. Phone use while driving-related crashes have been demonstrated to be an issue in rural areas, yet research into the impact of legal sanctions on phone use while driving has primarily focussed on urban areas. Therefore, this study aimed to investigate differences in enforcement of phone use while driving between rural and urban environments as reported by police officers. In addition, to provide necessary context, this study aimed to explore how the police officers perceive differences in drivers' engagement in phone use while driving between rural and urban environments. To address these aims, a total of 26 police officers from Queensland, Australia (18 with both rural and urban experience, 6 with only rural experience and 2 with only urban experience) completed an interview. A total of seven themes were developed from the data. Several differences between rural and urban environments were identified concerning different types of phone offending behaviour, as well as different resources, management and infrastructure that can impact police enforcement. For example, it was suggested that drivers in rural areas have less reasons to use their phone while driving. Nevertheless, when this behaviour does occur, it is more challenging to enforce this law in rural compared to urban environments. The results not only provide important contextual information for phone use while driving research, but also suggest that enforcement strategies for this behaviour may need to be recontextualised to incorporate the more nuanced aspects of rural policing.

Analysis of driver characteristics, self-reported psychology measures and driving performance measures associated with aggressive driving

Whereas aggressive driving mainly causes speed-related crashes, aggressive driving may be reduced to improve road safety by identifying aggressive driving behaviour, aggressive drivers' characteristics, and their underlying motivational and psychological processes. Previous studies show that both driving performance and self-reported measures of aggressive driving are effective means to identify aggressive drivers. However, these studies assessed aggressive driving patterns across only a limited number of events, did not relate driver characteristics to aggressive driving in each event, and used chiefly vehicle kinematics variables (e.g., mean speed), but not vehicle dynamics variables (e.g., brake pedal force) which better capture driver reaction and decision-making. To address these limitations, this study assessed driver characteristics, self-reported psychological measures, and driving performance measures associated with aggressive driving among 55 drivers' behaviours in 9driving events using a driving simulator and survey responses. The results of structural equation models showed that unique aggressive driving patterns and driver characteristics related to aggressive driving vary among different driving events. As such, we recommend road safety policies to reduce aggressive driving based on the findings in this study.

Is distraction on the road associated with maladaptive mobile phone use? A systematic review

Maladaptive Mobile Phone Use (MMPU) (also known as Smartphone Addiction, Nomophobia, Fear of Missing Out, or Problematic Mobile Phone Use) is a growing mental health problem. However, the health and safety consequences of MMPU remain unexplored in many real-life contexts. A potential setting where MMPU may have some negative repercussions is on the road. It is well established that road users (e.g., drivers, motorcyclists, pedestrians, and cyclists) increasingly injure themselves or others due to distractions such as phone use while on the road. Emerging research suggests that MMPU is a possible determinant of this risky behaviour. Therefore, it is essential to investigate the relationship between MMPU and mobile phone use behaviour on the road, as it could help guide and improve interventions aimed at increasing road safety. This systematic review investigated the relationship between maladaptive mobile phone use and mobile phone use behaviour on the road in terms of attitudes and risk perception, intention, phone use engagement, performance changes, and safety outcomes. A total of 44 studies were identified with 47 unique samples of road users, of which 68.1% (32/47) were comprised of drivers, 19.1% (9/47) were pedestrians, 8.5% (4/47) were unspecified road users, and there was one group of motorcyclists and cyclists. Our findings confirmed that MMPU is related to risky behaviour on the roads. In the 29 studies considering observed or self-reported behaviour, 90.9% (30/33) found that road users who scored higher in MMPU are more likely to use their phones on the road as cyclists, drivers, motorcyclists, and pedestrians. Of the nine studies that analysed performance changes, 55.6% (5/9) showed evidence that MMPU changes the performance of road users engaging in mobile phone use, meaning that there is evidence suggesting that MMPU determines the level of impairment. Of the nine studies that analysed the safety-related-outcomes, 66.7% (6/9) found that the higher the MMPU score, the more likely road users are to experience safety-critical traffic events. This review contributes to the literature by showing a pathway between the negative health consequences of MMPU and road trauma. We also identified that the quality of the studies was generally low due to study design and blinding aspects. This field of research also lacks standard practices as researchers avoid using established and well-validated questionnaires, often creating new ones to measure MMPU. This hinders the generalisability of the findings and raises questions about the construct validity and external validity of MMPU. The usefulness of future research would be enhanced by a consistent methodological approach using the same scales based on standard behavioural definitions. The cross-disciplinary nature of MMPU effects means that transport and road safety professionals need to work with healthcare professionals and technology organisations to understand and address MMPU as a contributing factor to road crashes.

Impact of Post-Covid-19 on driver behaviour: A perspective towards pandemic-sustained transportation

INTRODUCTION

With the announcement of novel Coronavirus disease 2019 (Covid-19) as a pandemic by World Health Organization (WHO) in March 2020, the whole world went into a lockdown that heavily affected human economic and social life. Since December 2020, with the discovery of effective vaccines, the world is now returning to some normality, particularly for those who are vaccinated. The multimodal transportation has resumed with majority of vaccinated drivers being back on road, driving to their work, and providing transport services. However, there are still several long-term Post-Covid-19 factors, affecting driver health and psychology.

METHODS

The study deployed a systematic search strategy and selected 62 research publications after rigorous evaluation of the literature. The review was based on (1) forming the inclusion and exclusion criteria, (2) selecting the appropriate keywords, and (3) searching of relevant publications and assessing the eligible articles.

RESULTS

A broad perspective study is carried out to gauge the impact of Post-Covid-19 scenarios on the driver physical health and mindset in the context of road safety and pandemic-sustained transportation. It was found that the Post-Covid-19 factors such as wearing face-mask during driving, taking oral anti-viral drugs, and fear of contracting disease, significantly impact the driver's performance and situation awareness skills. The analysis suggested that driver's health vitals and psychological driving awareness can be precisely detected through hybrid driver state monitoring methods.

CONCLUSIONS

The paper conducts a comprehensive review of the published work and provides unique research opportunities to counteract the challenges involved in precise monitoring of driver behaviour under the effects of different Post-Covid-19 factors. The perspective suggested the possible solutions to live with the pandemic in the context of pandemic-sustained transportation.

How distracting is chronic pain? The impact of chronic pain on driving behaviour and hazard perception

In road safety research, few studies have examined driving behaviour in chronic pain cohorts. The aim of this study was to investigate driving behaviour among drivers experiencing chronic pain. We compared individuals with chronic pain with age-gender matched healthy controls. Participants completed: (i) an anonymous online survey that included participant demographics, transport characteristics, self-reported driving behaviour, and pain characteristics (ii) a response-time hazard perception test and a verbal-response hazard prediction test for drivers, and (iii) a driving diary in which participants recorded their driving over two weeks. The results showed that participants with chronic pain were not significantly worse than controls for hazard perception and prediction test scores, self-reported attention-related errors, driving errors, driving violations, and involuntary distraction. Drivers with chronic pain did report significantly more driving lapses but this effect became non-significant when variables confounded with chronic pain, such as fatigue, were adjusted for. We also found that participants who reported particularly high levels of chronic pain performed worse in the hazard prediction test compared to the control group (and this effect could not be accounted for by other variables associated with chronic pain). In addition, participants with chronic pain reported significantly higher driving workload (mental demand, physical demand, effort, and frustration) compared with controls. The findings of this study provide new insights into driving behaviour in individuals with chronic pain and recommendations for future research in terms of driving assessment and self-regulation strategies are provided.

Road-safety-II: Opportunities and barriers for an enhanced road safety vision

Road safety research is largely focused on prediction and prevention of technical, human or organisational failures that may result in critical conflicts or crashes. Indicators of traffic risk aim to capture the passage to unsafe states. However, research in other industries has shown that it is meaningful to analyse safety along the whole spectrum of behaviours. Knowing the causes and patterns of "successful" interactions, rather than failures, could give new insights on the complexity of the system and the adaptability and resilience of its users in handling the inherent risks. The concept is known as Safety-II and has been extensively explored in the aviation, healthcare and process engineering domains. In this paper, we explore a new Safety-II paradigm for road safety research. We briefly review Safety-II applications in other sectors. We then present a Safety-II model for road safety, by means of an inverse version of Hyden's "safety pyramid". Furthermore, we discuss a number of key road safety goals, theories, analysis methods and data sources and map them into a tentative taxonomy of Safety-I and Safety-II applications. It is concluded that there can be opportunities and benefits from adopting this new mindset, in order to complement existing approaches.

Understanding sexual activity while driving as a form of distracted driving

Sexual activity while driving has been reported in emerging research. Sexual activity while driving is a form of distracted driving because it includes an individual (the driver) who deviates resources from the primary task (driving) towards a secondary task (sexual activity). However, most of our current knowledge about the range of sexual activities while driving is based on self-reported data or media reports. Thus, an in-depth understanding of sexual activities while driving and their interactions with non-sexual driving behaviours and vehicle control is missing. Additionally, there is limited information on the context of where sexual activities while driving occurs and the influence of factors such as the environment, the vehicle, interactions with other road users, and other in-vehicle distractions. To cover this gap, a content analysis of sexually explicit media (SEM) was conducted on a sample of 270 videos depicting real driving. We conducted descriptive analyses and used decision tree analysis to explore the association between sexual activities while driving and their interactions with non-sexual driving behaviours and vehicle control. The videos portrayed a naturalistic driving situation of a driver of a moving vehicle engaging in sexual activity. The results show that when engaging in sexual activity, drivers do not present safe vehicle control. Sexual activity imposes additional cognitive, physical, and visual demands on the driver, thereby decreasing safety. Similar to other distractions, drivers engaging in sexual activity while driving appear to mitigate risks. Concerning the potential for legal sanctions, it appears that drivers may attempt to conceal sexual activity by reducing their visible nudity and minimising interactions with other road users. Finally, mobile phones and cameras appear to interact with sexual activities while driving, by imposing potential restrictions on the range of sexual activities. Implications for policymakers and practitioners are discussed.

Objective assessment of trait attentional control predicts driver response to emergency failures of vehicular automation

With the advent of autonomous driving, the issue of human intervention during safety-critical events is an urgent topic of research. Supervisory monitoring, taking over vehicle control during automation failures and then bringing the vehicle to safety under time pressure are cognitively demanding tasks that pose varying difficulties across the driving population. This underpins a need to investigate individual differences (i.e., how people differ in their dispositional traits) in driver responses to automation system limits, so that autonomous vehicle design can be tailored to meet the safety-critical needs of higher-risk drivers. However, few studies thus far have examined individual differences, with self-report measures showing limited ability to predict driver takeover performance. To address this gap, the present study explored the utility of an established brain activity-based objective index of trait attentional control (frontal theta/beta ratio; TBR) in predicting driver interactions with conditional automation. Frontal TBR predicted drivers' average takeover reaction time, as well as the likelihood of accident after takeover. Moving towards practical applications, this study also demonstrated the utility of streamlined estimates of frontal TBR measured from the forehead electrodes and from a single crown electrode, with the latter showing better fidelity and predictive value. Overall, TBR is behaviourally relevant, measurable with minimal sensors and easily computable, rendering it a promising candidate for practical and objective assessment of drivers' neurocognitive traits that contribute to their AV driving readiness.

A systematic review of factors associated with illegal drug driving

Drug driving is a serious problem worldwide that can increase the risk of road crashes. This systematic review seeks to identify factors associated with drug driving (i.e., driving after consuming drugs other than alcohol) to highlight gaps in existing knowledge and inform the design of more effective countermeasures. A search of the literature was conducted for the period January 1, 2005 to July 31, 2021 using six different databases. The search protocol followed PRISMA guidelines and was registered in PROSPERO (#CRD42021234616). Studies that met inclusion criteria compared drug drivers with either non-drug drivers, alcohol-only drivers or drug drivers from an earlier time period, to identify factors specifically associated with drug driving, rather than common to all drivers. Two hundred and nineteen publications met the inclusion criteria and were included within the review. Based on the findings, a logic model was developed that presents the factors associated with drug driving. Various sociodemographic, psychosocial and legal factors emerged as the main factors associated with illegal drug driving. At the sociodemographic and psychological levels, drug drivers were more likely to be single, young males who often drive after using cannabis and who score high on sensation-seeking and impulsivity scales. The key social factor found to be associated with drug driving was peer acceptance/disapproval of the behaviour. At the legal level, the review suggested that the effectiveness of current enforcement approaches to drug driving vary among jurisdictions around the world due to differences in the level of perceived certainty of apprehension and the chances of punishment avoidance. Future research into the anticipated and actual rewards for drug driving is needed to inform the development of more effective countermeasures.

Impact of drivers on real-driving fuel consumption and emissions performance

Eco-driving has attracted great attention as a cost-effective and immediate measure to reduce fuel consumption significantly. Understanding the impact of driver behaviour on real driving emissions (RDE) is of great importance for developing effective eco-driving devices and training programs. Therefore, this study was conducted to investigate the performance of different drivers using a portable emission measurement system. In total, 30 drivers, including 15 novice and 15 experienced drivers, were recruited to drive the same diesel vehicle on the same route, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results show that novice drivers are less skilled or more aggressive than experienced drivers in using the accelerator pedal, leading to higher vehicle and engine speeds. As a result, fuel consumption rates of novice drivers vary in a slightly greater range than those of experienced drivers, with a marginally higher (2%) mean fuel consumption. Regarding pollutant emissions, CO and THC emissions of all drivers are well below the standard limits, while NO_x and PM emissions of some drivers significantly exceed the limits. Compared with experienced drivers, novice drivers produce 17% and 29% higher mean NO_x and PM emissions, respectively. Overall, the experimental results reject the hypothesis that driver experience has significant impacts on fuel consumption performance. The real differences lie in the individual drivers, as the worst performing drivers have significantly higher fuel consumption rates than other drivers, for both novice and experienced drivers. The findings suggest that adopting eco-driving skills could deliver significant reductions in fuel consumption and emissions simultaneously for the worst performing drivers, regardless of driving experience.

Investigating the effect of marking and delineation treatments on driver behavior at highway exit gore areas

Highway exit gore areas are common and essential components of highway networks everywhere. Drivers need to navigate, decelerate, and change lanes at exit gore areas through specified and compacted geometry. This makes exit gore areas potentially crash-prone locations. Studies analyzed factors contributing to crashes at exit gore areas. Although marking and delineation techniques can play a major role in enhancing safety, traffic control devices that serve this end were not given sufficient attention in recent research. Furthermore, the currently used marking and delineation treatments are widely different around the world and deploy devices of various forms, shapes, sizes, and colors. The Flemish Agency for Roads & Traffic (AWV) launched a study to explore the feasibility of adding colored and sizeable eye-catching objects, mounted or grounded exactly at the physical nose, to attract driver's attention and improve driving performance. The eye-tracking and driving behavior of 49 Belgian drivers was investigated in a driving simulator. Participants were also queried about the conspicuity of the control devices and their personal preferences. The results were univocal for situations including a guardrail. Using two mounted panels together, i.e., the horizontal and the vertical, scored better on all levels than the horizontal panel alone. The bigger surface size of the traffic control device significantly improved driving performance and was also favored by the participants. Situations without a guardrail lacked such clear results, which were mixed depending on the measure at hand. A larger size of a grounded object-marker, again, improved driver's performance. Findings concerning the colors red or green appeared to favor red, although this was less univocal. These findings are aimed to spark ideas for further research and to assist practitioners and policy-makers in better designing exit gore areas while achieving more consistency and safety.

A systematic review on sensor-based driver behaviour studies: coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions

In the plan and development of Intelligent Transportation Systems (ITS), understanding drivers behaviour is considered highly valuable. Reckless driving, incompetent preventive measures, and the reliance on slow and incompetent assistance systems are attributed to the increasing rates of traffic accidents. This survey aims to review and scrutinize the literature related to sensor-based driver behaviour domain and to answer questions that are not covered so far by existing reviews. It covers the factors that are required in improving the understanding of various appropriate characteristics of this domain and outlines the common incentives, open confrontations, and imminent commendations from former researchers. Systematic scanning of the literature, from January 2014 to December 2020, mainly from four main databases, namely, IEEEXplore, ScienceDirect, Scopus and Web of Science to locate highly credible peer-reviewed articles. Amongst the 5,962 articles found, a total of 83 articles are selected based on the author's predefined inclusion and exclusion criteria. Then, a taxonomy of existing literature is presented to recognize the various aspects of this relevant research area. Common issues, motivations, and recommendations of previous studies are identified and discussed. Moreover, substantial analysis is performed to identify gaps and weaknesses in current literature and guide future researchers into planning their experiments appropriately. Finally, future directions are provided for researchers interested in driver profiling and recognition. This survey is expected to aid in emphasizing existing research prospects and create further research directions in the near future.

How do older drivers perceive visual information under increasing cognitive load? Significance of personality on-road safety

The ability to properly receive information and respond to stimuli is a prerequisite for road safety. The aim of this study was to determine the changes in oculomotor activity under conditions of increasing cognitive load depending on personality traits in older drivers (65 years and above). We assessed 44 male active drivers (M = 69, SD = 8.1) in a road traffic simulator in the dual-task paradigm: n-back reaction test (central task) and memory test (peripheral task). During the test in the simulator, oculomotor activity was recorded. Drivers' personality traits were determined using the EPQ-R questionnaire. With the increase of cognitive load in drivers with high levels of neuroticism and extraversion, the time of saccades and fixation significantly increased. The decrease in the effectiveness of visual attention shifting in older drivers intensified as the difficulty of performing tasks increased and manifested itself in longer saccade and fixation times. A higher level of neuroticism and the resulting stress and emotional tension can translate into a greater tendency to make mistakes in older drivers.

Driver influence on vehicle trajectory prediction

Drivers continually interact with other road users and use information from the road environment to make decisions to control their vehicle. A clear understanding of different parameters impacting this interaction can provide us with a new design approach for a more effective driver assistance system - a personalised trajectory prediction system. This paper highlights the influential factors on trajectory prediction system performance by (i) identifying driver behaviours impacting the trajectory prediction system; and (ii) analysing other contributing factors such as traffic density, secondary task, gender and age group. To explore the most influential contributing factors, we first train an interaction-aware trajectory prediction system using time-series data derived from the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS). Prediction error is then analysed based on driver characteristics such as driver profile which is subjectively measured through self-reported questions, and driving performance which is based on evaluation of time-series information such as speed, acceleration, jerk, time, and space headway. The results show that prediction error significantly increased in the scenarios where the driver engaged in risky behaviour. Analysis shows that trajectory prediction system performance is also affected by factors such as traffic density, engagement in secondary tasks, driver gender and age group. We show that the driver profile, which is subjectively measured using self-reported questionnaires, is not as significant as the driving performance information, which is objectively measured and extracted during each specific driving scenario.

Low-cost road marking measures for increasing safety in horizontal curves: A driving simulator study

Statistics show that horizontal curves, especially those of radii less than 200 m, present an increased road accident risk mainly due to inappropriate speed and failure to maintain proper lateral position. This simulator study aims to analyse how two low-cost road marking measures (red median and horizontal warning signs), alone or combined with a vertical warning sign, affect driver behaviour (driving speed, lateral movement, acceleration/deceleration) before and throughout dangerous horizontal curves on a two-way rural road. With GIS-supported mapping of traffic accidents, we identified the most dangerous curves on the main rural road in Croatia and replicated them on the driving simulator. Based on the driving runs of 43 participants, the study concluded that both measures, used either alone or combined with a vertical warning sign, significantly reduced the speed compared to the control condition (vertical warning sign alone). Additionally, the use of a red median prompted the lateral movement of the vehicle closer to the edge line. The paper also defines the potential use of the measures for dealing with specific types of curve-related accidents.

Driver speed compliance following automatic incident detection: Insights from a naturalistic driving study

Automatic incident detection (AID) systems and variable speed limits (VSLs) can reduce crash probability and traffic congestion. Studies based on loop detector data have shown that AID systems decrease the variation in speeds between drivers. Despite the impact on driver behaviour characteristics, most mathematical models evaluating the effect of AID systems on traffic operations do not capture driver response realistically. This study examines the main factors related to driver speed compliance with a sequence of three VSLs triggered by an AID system. For this purpose, the variable speed limit database of the executive agency of the Dutch Ministry of Infrastructure and Water Management (Rijkswaterstaat) was integrated into the UDRIVE naturalistic driving database for passenger car data collected in the Netherlands. The video data were annotated to analyse driver glance behaviour and secondary task engagement. A logistic regression model was estimated to predict driver speed compliance after each VSL in the sequence. The results reveal that the factors predicting compliance to the VSLs differ based on which of the three VSLs the driver is subjected to. Low speeds and accelerations before the gantry, approaching a slower leader, high proportion of time with eyes-on-road and close consecutive gantries were associated with high compliance with the first VSL in the sequence (i.e., indicating a speed limit of 70 km/h with flashing attention lights). Low speeds and accelerations before the gantry, close consecutive gantries and a small number of lanes resulted in high compliance with the second VSL (i.e., a speed limit of 50 km/h with flashing attention lights). Low speeds before the gantry and close consecutive gantries were linked to high compliance with the third VSL (i.e., indicating a speed limit of 50 km/h). Although further investigations based on a larger sample are needed, these findings are relevant to the development of human-like driving assistance systems and of traffic simulations that assess the impact of AID systems on traffic operations realistically.

Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review

Several factors can influence driver behaviour, and road geometry is one of them. A better understanding of driver-roadway interaction can enhance road design to create a safer traffic system. In this context, driving simulators are powerful tools that combine convenience and effectiveness in identifying drivers' responses to different geometry factors. In this paper, a systematic review following a Prisma guideline was conducted on driving simulator studies that examined the effects of road geometry on driver behaviour to reveal the current procedures adopted in this field and their main findings. A systematic search of eleven databases was performed covering six years of research results. Inclusion of relevant studies focused on horizontal curves, a topic identified as the most cited, extended this period. The results revealed significant heterogeneity in relation to the measured variables and deficiencies when reporting the experiment, which prevented a meta-analysis of the studies' outcomes. Despite this, a discussion of the potential of driving simulators to contribute to several road safety research gaps is presented. In addition, problems of a lack of standardisation in the performance of the experiments were detected, potentially influencing the findings of the studies. However, the results also suggest that experiments that followed good experimental practices observed effects on driver performances not detected by other studies.

How do oncoming traffic and cyclist lane position influence cyclist overtaking by drivers?

Overtaking cyclists is challenging for drivers because it requires a well-timed, safe interaction between the driver, the cyclist, and the oncoming traffic. Previous research has investigated this manoeuvre in different experimental environments, including naturalistic driving, naturalistic cycling, and simulator studies. These studies highlight the significance of oncoming traffic-but did not extensively examine the influence of the cyclist's position within the lane. In this study, we performed a test-track experiment to investigate how oncoming traffic and position of the cyclist within the lane influence overtaking. Participants overtook a robot cyclist, which was controlled to ride in two different lateral positions within the lane. At the same time, an oncoming robot vehicle was controlled to meet the participant's vehicle with either 6 or 9 s time-to-collision. The order of scenarios was randomised over participants. We analysed safety metrics for the four different overtaking phases, reflecting drivers' safety margins to rear-end, head-on, and side-swipe collisions, in order to investigate the two binary factors: 1) time gap between ego vehicle and oncoming vehicle, and 2) cyclist lateral position. Finally, the effects of these two factors on the safety metrics and the overtaking strategy (either flying or accelerative depending on whether the overtaking happened before or after the oncoming vehicle had passed) were analysed. The results showed that, both when the cyclist rode closer to the centre of the lane and when the time gap to the oncoming vehicle was shorter, safety margins for all potential collisions decreased. Under these conditions, drivers-particularly female drivers-preferred accelerative over flying manoeuvres. Bayesian statistics modelled these results to inform the development of active safety systems that can support drivers in safely overtaking cyclists.

"It is frustrating to not have control even though I know it's not legal!": A mixed-methods investigation on applications to prevent mobile phone use while driving

Mobile phone distracted driving is a major risk factor for crashes. However, this behaviour has been increasing in recent years. Effective enforcement of mobile phone bans while driving faces several obstacles; as such, it is important to consider additional countermeasures. Applications designed to prevent distracted driving are a promising solution, yet more research is needed that examines their effectiveness in reducing dangerous phone use while driving behaviours. Additionally, these applications are voluntary in nature; therefore, an understanding of drivers' perceptions of the applications is necessary to determine how to improve uptake. A mixed methods design was utilised to examine these factors in a comprehensive manner. A total of 40 participants used the smartphone application "Do Not Disturb While Driving" for iOS phone operating systems or "Android Auto" for Android phone operating systems for approximately one week and completed three diary entries reporting on their experience. Two questionnaires that examined phone use while driving behaviours were also administered to participants; one before and one after completing the study. The quantitative results found that engagement in 1) visual-manual, 2) cognitive-auditory and 3) music mobile phone interactions significantly decreased while using the application. Distraction engagement and mental workload while driving also significantly decreased while using the application. The qualitative results identified a number of areas of improvement that need to be addressed, e.g. activation of the application and Bluetooth connection reliability. The features that required improvement presented an obstacle for effective use of the applications, and in some cases resulted in drivers deciding to stop using the application. Positive perceptions of the application were associated with the experiences of the application functioning appropriately and activating automatically. These results show that applications designed for voluntary use to prevent mobile phone distracted driving are a promising countermeasure, although current applications require several improvements.

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.

Driver and road characteristics associated with child pedestrian injuries

BACKGROUND

Child pedestrians make up a significant proportion of all road traffic deaths. Our primary objective was to examine the association of driver characteristics with child pedestrian injuries with a secondary objective to broadly describe the road characteristics surrounding these collisions.

METHODS

We included drivers involved in child (<18 years old) pedestrian motor-vehicle collisions (PMVCs) in Calgary and Edmonton, Alberta (2010-2015). These drivers were compared with not at fault (Alberta adaptation of a Canadian culpability scoring tool) drivers involved in vehicle-only collisions. The data were analyzed with unconditional logistic regression.

RESULTS

Seven hundred ninety-three drivers collided with 826 children. One quarter of child PMVC drivers were 40-54 years old (25.2%). Younger drivers, 16-24 (adjusted odds ratio [aOR] = 1.62, 95% CI: 1.27-2.09), and older drivers, ≥55 (aOR = 1.57, 95% CI: 1.24-1.99) were more likely to be involved in a child PMVC. Time of day between 06:01 - 09:00 (aOR = 1.46, 95% CI: 1.16-1.85) and 18:01 - 24:00 (aOR = 1.68, 95% CI: 1.30-2.17), no seatbelt use (aOR = 2.30, 95% CI: 1.09-4.85), having a child passenger in the vehicle (aOR = 2.15, 95% CI: 1.56-2.96), and impairment including 'had been drinking' (aOR = 7.70, 95% CI: 2.85-20.86) and 'fatigued/asleep/medical defect' (aOR = 27.15, 95% CI: 8.30-88.88) were also associated with being a driver involved in a child PMVC.

CONCLUSIONS

Age, time, impairment and distraction were risk factors for being a driver involved in a child PMVC. Because child PMVC driver characteristics differ from the general driver population, driver-based interventions are a rational additional means of preventing child PMVCs.

Risk of automated driving: Implications on safety acceptability and productivity

Autonomous Vehicles have captured the imagination of our society and have promised a future of safe and efficient mobility. However, there is a need to understand behaviour and its consequences in the use of autonomous vehicles. Using paradigms of behavioural and experimental economics, we show that risk attitudes play a role in acceptability of autonomous vehicles, productivity in autonomous vehicles and safety under risk of failures of autonomous systems. We found that risk attitudes and age have a significant impact on these. We believe these findings will help provide guidance to insurance agencies, licensing, vehicle design, and policies around automated vehicles.

A trial of retrofitted advisory collision avoidance technology in government fleet vehicles

In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of seven months. The system provided headway monitoring, lane departure, forward collision and pedestrian collision warnings, using audio and visual alerts. The purpose of the trial was to determine whether the technology could change the driving behaviour of fleet vehicle drivers and improve their safety. The evaluation consisted of three components: (1) analysis of objective data to examine effects of the technology on driving behaviour, (2) analysis of video footage taken from a sample of the vehicles to examine driving circumstances that trigger headway monitoring and forward collision warnings, and (3) a survey completed by 122 of the 199 individuals who drove the trial vehicles to examine experiences with, and attitudes to, the technology. Analysis of the objective data found that the system resulted in changes in behaviour with increased headway and improved lane keeping, but that these improvements dissipated once the warning alerts were switched off. Therefore, the system is capable of altering behaviour but only when it is actively providing alerts. In-vehicle video footage revealed that over a quarter of forward collision warnings were false alarms, in which a warning event was triggered despite there being no vehicle travelling ahead. The surveyed drivers recognised that the system could improve safety but most did not wish to use it themselves as they found it to be distracting and felt that it would not prevent them from having a crash. The results demonstrate that collision avoidance technology can improve driving behaviour but drivers may need to be educated about the potential benefits for their driving in order to accept the technology.

Coming back into the loop: Drivers' perceptual-motor performance in critical events after automated driving

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 ≈0.3s^-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.

Is it really good to talk? Testing the impact of providing concurrent verbal protocols on driving performance

Questions have been raised regarding the impact that providing concurrent verbal protocols has on task performance in various settings; however, there has been little empirical testing of this in road transport. The aim of this study was to examine the impact of providing concurrent verbal protocols on driving performance. Participants drove an instrumented vehicle around a set route, twice whilst providing a concurrent verbal protocol, and twice without. A comparison revealed no differences in behaviour related to speed, braking and steering wheel angle when driving mid-block, but a significant difference in aspects of braking and acceleration at roundabouts. When not providing a verbal protocol, participants were found to brake harder on approach to a roundabout and accelerate more heavily coming out of roundabouts. It is concluded that providing verbal protocols may have a positive effect on braking and accelerating. Practical implications related to driver training and future research are discussed. Practitioner Summary: Verbal protocol analysis is used by ergonomists to understand aspects of cognition and decision-making during complex tasks such as driving and control room operation. This study examines the impact that it has on driving performance, providing evidence to support its continued use in ergonomics applications.

Transition to manual: Comparing simulator with on-road control transitions

BACKGROUND

Whilst previous research has explored how driver behaviour in simulators may transfer to the open road, there has been relatively little research showing the same transfer within the field of driving automation. As a consequence, most research into human-automation interaction has primarily been carried out in a research laboratory or on closed-circuit test tracks.

OBJECTIVE

The aim of this study was to assess whether research into non-critical control transactions in highly automated vehicles performed in driving simulators correlate with road driving conditions.

METHOD

Twenty six drivers drove a highway scenario using an automated driving mode in the simulator and twelve drivers drove on a public motorway in a Tesla Model S with the Autopilot activated. Drivers were asked to relinquish, or resume control from the automation when prompted by the vehicle interface in both the simulator and on road condition.

RESULTS

Drivers were generally faster to resume control in the on-road driving condition. However, strong positive correlations were found between the simulator and on road driving conditions for drivers transferring control to and from automation. No significant differences were found with regard to workload, perceived usefulness and satisfaction between the simulator and on-road drives.

CONCLUSION

The results indicate high levels of relative validity of driving simulators as a research tool for automated driving research.

Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers

The use of mobile phones while driving remains a major human factors issue in the transport system. A significant safety concern is that driving while distracted by a mobile phone potentially modifies the driving speed leading to conflicts with other road users and consequently increases crash risk. However, the lack of systematic knowledge of the mechanisms involved in speed adaptation of distracted drivers constrains the explanation and modelling of the extent of this phenomenon. The objective of this study was to investigate speed adaptation of distracted drivers under varying road infrastructure and traffic complexity conditions. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated road with different traffic conditions, such as free flow traffic along straight roads, driving in urbanized areas, and driving in heavy traffic along suburban roads. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. To understand the relationships between distraction, road infrastructure and traffic complexity, speed adaptation calculated as the deviation of driving speed from the posted speed limit was modelled using a decision tree. The identified groups of road infrastructure and traffic characteristics from the decision tree were then modelled with a Generalized Linear Mixed Model (GLMM) with repeated measures to develop inferences about speed adaptation behaviour of distracted drivers. The GLMM also included driver characteristics and secondary task demands as predictors of speed adaptation. Results indicated that complex road environments like urbanization, car-following situations along suburban roads, and curved road alignment significantly influenced speed adaptation behaviour. Distracted drivers selected a lower speed while driving along a curved road or during car-following situations, but speed adaptation was negligible in the presence of high visual cutter, indicating the prioritization of the driving task over the secondary task. Additionally, drivers who scored high on self-reported safe attitudes towards mobile phone usage, and who reported prior involvement in a road traffic crash, selected a lower driving speed in the distracted condition than in the baseline. The results aid in understanding how driving task demands influence speed adaptation of distracted drivers under various road infrastructure and traffic complexity conditions.

Driver sleepiness on YouTube: A content analysis

Driver sleepiness is a major contributor to severe crashes and fatalities on our roads. Many people continue to drive despite being aware of feeling tired. Prevention relies heavily on education campaigns as it is difficult to police driver sleepiness. The video sharing social media site YouTube is extremely popular, particularly with at risk driver demographics. Content and popularity of uploaded videos can provide insight into the quality of publicly accessible driver sleepiness information. The purpose of this research was to answer two questions; firstly, how prevalent are driver sleepiness videos on YouTube? And secondly, what are the general characteristics of driver sleepiness videos in terms of (a) outlook on driver sleepiness, (b) tone, (c) countermeasures to driver sleepiness, and, (d) driver demographics. Using a keywords search, 442 relevant videos were found from a five year period (2nd December 2009-2nd December 2014). Tone, outlook, and countermeasure use were thematically coded. Driver demographic and video popularity data also were recorded. The majority of videos portrayed driver sleepiness as dangerous. However, videos that had an outlook towards driver sleepiness being amusing were viewed more often and had more mean per video comments and likes. Humorous videos regardless of outlook, were most popular. Most information regarding countermeasures to deal with driver sleepiness was accurate. Worryingly, 39.8% of videos with countermeasure information contained some kind of ineffective countermeasure. The use of humour to convey messages about the dangers of driver sleepiness may be a useful approach in educational interventions.

Driver behaviour at roadworks

There is an incompatibility between how transport engineers think drivers behave in roadworks and how they actually behave. As a result of this incompatibility we are losing approximately a lane's worth of capacity in addition to those closed by the roadworks themselves. The problem would have little significance were it not for the fact a lane of motorway costs approx. £30 m per mile to construct and £43 k a year to maintain, and that many more roadworks are planned as infrastructure constructed 40 or 50 years previously reaches a critical stage in its lifecycle. Given current traffic volumes, and the sensitivity of road networks to congestion, the effects of roadworks need to be accurately assessed. To do this requires a new ergonomic approach. A large-scale observational study of real traffic conditions was used to identify the issues and impacts, which were then mapped to the ergonomic knowledge-base on driver behaviour, and combined to developed practical guidelines to help in modelling future roadworks scenarios with greater behavioural accuracy. Also stemming from the work are novel directions for the future ergonomic design of roadworks themselves.

Drowsy drivers' under-performance in lateral control: How much is too much? Using an integrated measure of lateral control to quantify safe lateral driving

Internationally, drowsy driving is associated with around 20% of all crashes. Despite the development of different detection methods, driver drowsiness remains a disconcerting public health issue. Detection methods can estimate drowsiness by directly measuring the physiology of the driver, or they can measure the effect that drowsiness has on the state of the vehicle due to the behavioural changes that drowsiness elicits in the driver. The latter has the benefit that it could measure the net effect that drowsiness has on driving performance which links to the actual safety risk. Fusing multiple sources of driving performance indicators like lane position and steering wheel metrics in order to detect drowsiness has recently gained increased attention. However, not much research has been conducted with regard to using integrated measures to detect increased drowsiness within an individual driver. Different levels of drowsiness are also rarely classified in terms of safe or unsafe. In the present study, we attempt to slowly induce drowsiness using a monotonous driving task in a simulator, and fuse lane position and steering wheel angle data into a single measure for lateral control performance. We argue that this measure is applicable in real-time detection systems, and quantitatively link it to different levels of drowsiness by validating it to two established drowsiness metrics (KSS and PERCLOS). Using level of drowsiness as a surrogate for safety we are then able to set simple criteria for safe and unsafe lateral control performance, based on individual driving behaviour.

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18-26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33s in time headway when a driver is engaged in hands-free phone conversation and a 0.75s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Pedestrian crossing situations: quantification of comfort boundaries to guide intervention timing

INTRODUCTION

Technical systems that warn or brake for vehicle-pedestrian encounters reduce injuries more effectively the earlier an intervention is initiated. However, premature intervention can irritate drivers, leading to system deactivation and, consequently, no injury reduction whatsoever. It has been proposed that no intervention should be initiated as long as attentive drivers are within their comfort zones. This study aims at quantifying driver comfort boundaries for pedestrian crossing situations to offer guidance for the appropriate timing of interventions.

METHODS

Sixty two volunteers drove through an intersection on a test track at 30 and 50km/h. A pedestrian dummy was launched from behind an obstruction towards the driving path of the approaching car. Brake onset indicated discomfort. Time to collision (TTC), longitudinal and lateral distance were measured at brake onset.

RESULTS

TTC was independent of driving speed ranging from 2.1 to 4.3s with a median of 3.2s. Longitudinal distance ranged from 19 to 48 meters with an apparent difference between driving speeds. Lateral distances differed slightly, but significantly between driving speeds. The median was 3.1m (3.2m for 30km/h and 2.9m for 50km/h) and values ranged from 1.9 to 4.1m. Lateral distance in seconds ranged from 1.9 to 4.3s with a median value of 3.1s (3.2s for 30km/h and 3.0s for 50km/h).

DISCUSSION

TTC was independent of driving speed, trial order and volunteer age. It might be considered suitable to intervene in situations where, for example, 90% of drivers have exceeded their comfort boundary, i.e. when drivers have already initiated braking. This percentile value translates to intervention at a TTC of 2.5s (95% confidence 2.4-2.7s). The study was limited to Swedish nationals, fully aware drivers, and two driving speeds, but did not investigate behavioural changes due to system interaction.

CONCLUSION

This study showed that TTC at brake onset was a suitable measure for the quantification of driver comfort boundaries in pedestrian crossing situations. All drivers applied their brakes prior to 2.1s TTC.

Microsimulation modelling of driver behaviour towards alternative warning devices at railway level crossings

Level crossings are amongst the most complex of road safety issues, due to the addition of rail infrastructure, trains and train operations. The differences in the operational characteristics of different warning devices together with varying crossing, traffic or/and train characteristics, cause different driver behaviour at crossings. This paper compares driver behaviour towards two novel warning devices (rumble strips and in-vehicle audio warning) with two conventional warning devices (flashing light and stop sign) at railway level crossings using microsimulation modelling. Two safety performance indicators directly related to collision risks, violation and time-to-collision, were adopted. Results indicated the active systems were more effective at reducing likely collisions compared to passive devices. With the combined application of driving simulation and traffic microsimulation modelling, traffic safety performance indicators for a level crossing can be estimated. From these, relative safety comparisons for the different traffic devices are derived, or even for absolute safety evaluation with proper calibration from field investigations.

Re-conceptualising the reckless driving behaviour of young drivers

Reckless driving is a major contributing factor to road morbidity and mortality. While further research into the nature and impact of reckless driving, particularly among young people, is urgently needed, the measurement of reckless driving behaviour also requires increased attention. Three major shortcomings apparent in established measures of driver behaviour are that they do not target the full range of reckless driving behaviours, they measure characteristics other than driving behaviours, and/or they fail to categorise and label reckless driver behaviour based on characteristics of the behaviours themselves. To combat these shortcomings, this paper reports the development and preliminary validation of a new measure of reckless driving behaviour for young drivers. Exploratory factor analysis of self-reported driving data revealed four, conceptually distinct categories of reckless driving behaviour: those that increase crash-risk due to (a) distractions or deficits in perception, attention or reaction time (labelled "distracted"), (b) driving under the influence of drugs or alcohol (labelled "substance-use"), (c) placing the vehicle in an unsafe environment beyond its design expectations (labelled "extreme"), and (d) speed and positioning of the vehicle relative to other vehicles and objects (labelled "positioning"). Confirmatory factor analysis of data collected from a separate, community sample confirmed this four-factor structure. Multiple regression analyses found differences in the demographic and psychological variables related to these four factors, suggesting that interventions in one reckless driving domain may not be helpful in others.

Safe mobility for elderly drivers--considerations based on expert and self-assessment

To further understand the needs of the growing population of elderly drivers and create solutions for safe mobility it is important to understand the driving scenarios and aspects in day to day traffic that may be of challenge for this group. More so, individual differences in how drivers perceive their own driving ability may have an effect on how individuals limit their mobility and/or increase their exposure to risk situations, with a potential negative effect on safety. In this study two sets of assessments have been used in order to identify scenarios and aspects needing consideration in creating safe mobility for elderly drivers; an expert assessment using on-road driving together with assessments through semi structured in-depth interviews. This combination also enables categorisation of the drivers, comparing their own perception of their driving performance with the expert assessment based on actual on-road driving. Four different categories of drivers were identified: adequate (positive), over, under and adequate (negative) estimators. A number of important aspects were identified in the study. Adapting speed to the situation and driving too fast, especially on straight roads in the city, is one aspect. Seeking the attention of other road users at intersections and roundabouts is another important consideration identified. Awareness of difficulties related to speed adaptation and attention was low amongst all the driver categories. However, a difference in attitude was seen in the categories with a more humble and acceptant attitude amongst the adequate and under estimator groups, as compared to the over estimators suggesting that the aspect of attitudes is another important factor for consideration.

Culture related to road traffic safety: a comparison of eight countries using two conceptualizations of culture

The majority of previous cross-country studies of human factors relevant to traffic safety have not operationalized and measured culture. Also studies in this vein have mostly been carried out in Europe and the United States. The aim of the study was to examine country cluster differences, based on the Culture's Consequences framework, in road traffic risk perception, attitudes towards traffic safety and driver behaviour in samples from Norway, Russia, India, Ghana, Tanzania, Uganda, Turkey and Iran. An additional aim was to examine cluster differences in road traffic culture as symbol use and to investigate whether this theoretical cultural framework predicts risk perception, attitudes towards traffic safety and driver behaviour in the country clusters. The sample consisted of a total of 2418 individuals who were obtained by convenience sampling in the different countries. The countries segmented into four Culture's Consequences clusters; Norway, Russia and India, Sub-Saharan Africa, and Near East countries. The findings showed that Norwegians reported overall safer attitudes towards traffic safety and driver behaviour than the remaining country clusters. Individuals in Africa reported the highest risk perception. The countries also differed substantially in road traffic culture as symbol use. Contrary to established cultural theory, prediction models revealed that cultural factors were stronger predictors of driver behaviour than of risk perception. Also, the social cognitive risk constructs (i.e. risk perception and attitudes) solely explained variance in driver behaviour in the Norwegian and Russia/India clusters. Previous empirical efforts, which aimed to demonstrate that culture is important for the risk perception criterion, may have focused on a criterion variable that is not strongly related to driver behaviour. Furthermore, countermeasures aimed to influence social cognition may have stronger applicability in countries with a more individualistic western cultural orientation.

Changes in self-reported driving intentions and attitudes while learning to drive in Great Britain

Novice drivers are overrepresented in traffic collisions, especially in their first year of solo driving. It is widely accepted that some driving behaviours (such as speeding and thrill-seeking) increase risk in this group. Increasingly research is suggesting that attitudes and behavioural intentions held in the pre-driver and learning stage are important in determining later driver behaviour in solo driving. In this study we examine changes in several self-reported attitudes and behavioural intentions across the learning stage in a sample of learner drivers in Great Britain. A sample of 204 learner drivers completed a self-report questionnaire near the beginning of their learning, and then again shortly after they passed their practical driving test. Results showed that self-reported intentions regarding speed choice, perceptions regarding skill level, and intentions regarding thrill-seeking (through driving) became less safe over this time period, while self-reported intentions regarding following distance and overtaking tendency became safer. The results are discussed with reference to models of driver behaviour that focus on task difficulty; it is suggested that the manner in which behind-the-wheel experience relates to the risk measures of interest may be the key determining factor in how these change over the course of learning to drive.

An on-road network analysis-based approach to studying driver situation awareness at rail level crossings

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.

Exploring older drivers' perceptions of driving

This research uses grounded theory to assess the driving needs of 29 older car drivers using four data collection techniques (two waves of focus groups, an interview and a driver diary). Findings suggest that older drivers view themselves as having better driving skills and attitude towards driving compared to when they were younger and compared to other drivers. In addition, they have a good ability to adapt to their changing physiology. Nevertheless, they report difficulty in assessing their own driving ability and cite they would like help to increase self-awareness about the driving task. In addition, the participants report having increasing difficulty in not having enough time to read, compute and comprehend road signs, maintaining a constant speed at the speed-limit, increased tiredness and fatigue and increased sensitivity to glare. The findings suggest given an iterative, qualitative methodology where driving issues are focused upon, older drivers can become more self-aware of their driving limitations and discuss these aspects in the context of ageing physiology.

Driving errors, driving violations and accident involvement

A survey of over 1600 drivers is reported, the results of which are consistent with those reported in an earlier study (Reason et al. 1990), which identified a three-fold typology of aberrant driving behaviours. The first type, lapses, are absent-minded behaviours with consequences mainly for the perpetrator, posing no threat to other road users. The second type, errors, are typically misjudgements and failures of observation that may be hazardous to others. The third type, violations, involve deliberate contraventions of safe driving practice. In the present study the survey instrument used, the Driver Behaviour Questionnaire, was also shown to be reliable over time. Each type of behaviour was found to have different demographic correlates. Most importantly, accident liability was predicted by self-reported tendency to commit violations, but not by tendency to make errors or to have lapses. The implications for road safety are discussed.