Accidents related to insufficient road grip in Sweden have historically been investigated for winter conditions, where substantial effect on passenger car accident risk from different types of tyres has been observed. Grip-related accidents during summer conditions have so far primarily focused on the effect of Electronic Stability Control (ESC), with no assessment of possible influence from tyre properties. The use of winter tyres during summer has been increasing among passenger cars in Sweden and is currently estimated to be around 7%. Tyre tests indicate 20%–40% longer braking distances for winter tyres compared to summer tyres, and statistics have indicated that passenger cars with winter tyres are heavily overrepresented among the fatal accidents during the summer period in Sweden. The purpose of this study has therefore been to estimate the potential risk increase for a fatal grip-related accident for passenger cars using winter tyres, compared to summer tyres, during summer. Statistics from in-depth studies of fatal road accidents in Sweden from the 10-year period 2012–2021 was used in an induced exposure risk analysis, with a complementary stratified analysis investigating the effect of possible confounding factors. The results indicate that the overrepresentation among fatal accidents of cars equipped with winter tyres during the summer period to a large extent is related to the inferior road grip of winter tyres. The risk increase was particularly high for fatal grip related accidents when driving within the regulated speed limit. Tyre properties have generally been neglected as a contributing factor among fatal accidents occurring in the summer period in the Swedish in-depth studies. The present study shows that tyres have a substantial impact on grip-related fatal accidents with passenger cars in Sweden during the summer period, which account for 25% of the fatal accidents involving passenger cars. This highlights the need for increased attention to tyre properties in accident investigations. The results are most likely relevant also to other countries where winter tyres are used and the findings should be addressed by policy makers and other stakeholders.
Widespread and common usage of bicycles makes cycling safety a critical issue, as over the years, cyclists’ injuries and fatalities have been rising. The majority of cycling safety literature justifiably focuses on the dangers posed by motor vehicles; however, single-bicycle crashes (SBCs) are a major portion of injuries and hospitalisations in the Netherlands. To address this gap, this study has a twofold objectives: 1) to compare SBCs and Non-SBCs in the police- and ambulance-reported crash datasets, and 2) to identify and examine different factors contributing to SBCs and Non-SBCs at urban intersections with 30 km/h and 50 km/h speed limits. For this purpose, we compared SBCs with non-SBCs (cyclist crashes involving other vehicles) by modelling the cyclist crash occurrence at urban intersections. This allowed estimating the effects of different factors associated with the built environment, infrastructure, and traffic exposure. To address the underreporting problem associated with police-reported datasets, we used ambulance dataset collected at the Flevoland region of the Netherlands. Results revealed that traffic and cycling volumes, as well as cycling infrastructure, have the most impact on increasing bicycle-involved crash counts. Furthermore, proximity to destinations is proved to be relevant, depending on the specific destination and type of crash it has an effect on. Traffic volume showed to be most relevant for Non-SBCs at 50 km/h roads, while cycling infrastructure had an important effect both on SBCs and Non-SBCs.
Driving anger is known to be associated with aggressive driving, which can lead to a higher probability of accidents. Since the Driving Anger Scale (DAS) was first introduced in the US, different versions of the scale have been used in many countries to measure anger evoked by different traffic situations. The first aim of this study was to test the validity and reliability of the UK-DAS in Iran. The second aim was to examine the relationship between demographic factors and the DAS factors found in Iran. A total of 409 questionnaires were completed by Iranian drivers, out of which, 205 were used for exploratory factor analysis and 204 were used for confirmatory factor analysis. The results revealed a reliable four-factor structure in Iran including 19 of the original 21 items from the UK-DAS. These four factors were interpreted as discourtesy, direct hostility, reckless driving and progress impeded. Further analyses showed that younger, compared to older, participants scored higher on driving anger evoked by other road users’ discourtesy and direct hostile behaviours. With the factor structure validated in Iran the DAS can now be used in further research, for example to examine how Iranian drivers express their anger in different traffic situations. Cross-culturally, the results can be compared with other countries.
There is limited contemporary evidence on head impact conditions and injuries in motorcyclists, despite substantial recent changes in vehicles, helmet design and test standards. This constrains evidence-driven improvements to helmet protection and impact test protocols, particularly for underrepresented facial impacts. We quantified head impact locations and associated head and facial injury distributions in 12 years of motorcycle collisions from Great Britain’s Road Accident In-Depth Studies (RAIDS) database (1 April 2013–31 March 2025). Injuries were classified using Abbreviated Injury Scale codes augmented with free-text identification of clinically utilised Mayo-classified brain injury, and primary helmet impact location was derived from investiga-tor summaries and helmet photographs. Most of the 353 motorcyclists were injured (93%) and male (90%), and 2% were unhelmeted. One third sustained at least one head injury and 24.9% sustained Mayo-classified traumatic brain injury (19.0% moderate–severe). Facial injuries occurred in 12.2%, including 4.4% with facial fracture. Skull fractures (including basilar) and intracranial haemorrhage were also common. Head and facial injuries were more prevalent in fatally injured motorcyclists than survivors. Primary helmet impact location was determined for 125 motorcyclists with 50.4% of impacts were to the facial region. Head injury rates and patterns were similar across primary impact locations. When primary facial impacts caused head injury, upper face and chinbar impacts dominated visor impacts. Facial impacts are both frequent and associated with clinically important head injuries. Helmet standards and consumer ratings should incorporate facial impact assessments and adopt injury risk criteria re-flecting skull fractures, focal brain injury and intracranial haemorrhage.
Right turns at urban intersections pose a significant risk to cyclists, but existing infrastructure-based warning systems often suffer from high false alarm rates and a lack of specificity. Following a PICO-based research design, this study addresses the research question of whether targeted acoustic warnings using beamforming technology can effectively warn cyclists (target) while simultaneously minimizing the disturbance for pedestrians and residents (non-targets). Using a fully immersive VR environment with spatial audio simulations and realistic traffic noise sounds, the study examined how cyclists, pedestrians, and residents perceive and accept these targeted signals. The experiment compared different warning sounds at varying distances from the intersection to determine their perceptibility and effectiveness. The results show that while all acoustic warnings were reliably perceived as relevant, verbal warnings proved to be the most effective, as speech is immediately understood regardless of the cyclist's distance from the intersection. In terms of environmental impact, the study found that beamforming can significantly minimize disturbance to pedestrians and residents, with narrow-beam signals perceived as the least disturbing. This work contributes to this field of research by demonstrating that spatially controlled acoustic systems offer a more specific and socially acceptable solution for protecting vulnerable cyclists than conventional omnidirectional or purely visual methods. By combining technical precision with intuitive communication, this approach effectively counteracts the “cry wolf” effect and improves overall road safety.
Transportation-related injuries remain one of the leading causes of mortality among children and youth in Canada. Factors such as age, sex, marginalization, and the COVID-19 pandemic may influence children’s interactions with their environment and their mobility patterns. The objectives of this study were to describe: (1) the incidence of transport-related emergency department (ED) visits and hospitalizations in Ontario by type (motor vehicle, pedestrian, cycling) and by age and sex; and (2) the temporal trends in transport-related health service utilization by type and level of marginalization over time, including during the COVID-19 pandemic. Data for all traffic and non-traffic motor vehicle and vulnerable road user injuries (VRU, pedestrians and cyclists) were obtained for ED visits and hospitalizations in Ontario from January 2015 to March 2022. Descriptive analyses were completed by age group, sex, and marginalization across the study period. A simulation approach using Bayesian Poisson regression was employed to examine how the pandemic affected temporal trends. During the study period, the rate per 10 000 children and youth with motor vehicle-related injuries was 328 (95% CI: 325–331), and for VRU-related injuries was 275 (95% CI: 272.4–277). Sixty-one percent of cyclist ED visits and hospitalizations were non-traffic related. Males, children and youth aged 10–19 and more marginalized children generally had higher rates of both ED visits and hospitalizations than females, children aged 0–9 and those less marginalized. At the onset of the pandemic, ED visits for traffic-related motor vehicle and all pedestrians were lower than expected, and non-traffic motor vehicle and all cyclists were higher than expected. The greatest differences from expected in ED visits were in the least marginalized children; for example, there was a 107% increase in cyclist non-traffic in the least marginalized versus 11% increase in the most marginalized quintile. The findings of this study reinforce the ongoing need to focus on cycling safety, particularly non-traffic-related, for children and youth. These findings can also inform future equitable injury preventive efforts in light of significant population-level events, such as pandemics, that might change children’s mobility patterns.
Road traffic injuries remain a major public health concern in Pakistan and other low- and middle-income countries, where driver behaviour is a dominant crash-contributing factor. However, limited multi-city evidence exists on how demographic characteristics jointly influence aberrant driving across different dimensions. This study investigates the associations among age, gender, and driving experience, and four dimensions of aberrant driving behaviour—risky, aggressive, distracted, and unlawful—using a cross-sectional survey of 400 drivers from 10 major urban centers in Punjab, Pakistan. A Driver Behaviour Questionnaire (DBQ)-based instrument was used to construct composite indices, and descriptive statistics, independent-samples t-tests, one-way analysis of variance, and multiple linear regression were applied. Risky driving had the highest mean score (3.81 on a five-point scale), with higher levels among drivers with ≥10 years of experience (mean = 4.02). Younger drivers reported higher levels of aggressive behaviour, while male drivers exhibited higher levels of aggressive, distracted, and unlawful behaviour. The findings indicate that dangerous driving in Pakistan is not limited to young drivers but extends to middle-aged and experienced drivers. This study contributes to road-safety literature by providing multi-city, disaggregated DBQ-based evidence from Pakistan, showing that demographic effects are not uniform across aberrant-driving dimensions and that risky and unlawful behaviours are not confined to young or inexperienced drivers but also extend to middle-aged and experienced drivers.
In-built Network-wide Road Safety Assessment (IRSA) procedures involve the visual inspection of road design characteristics, and assigning scores to sections of the road network based on the availability and condition of the road characteristics. The main objective of the study was to evaluate two IRSA methodologies developed for rural highways, that is the Simplified methodology, and the Networkwide Proactive methodology (NWA Proactive). Both methodologies are applied on a 10.41 km, twolane undivided rural road section in Latina Province, Italy. The assessment focused on comparing the reliability and predictive performance of these methods. The results revealed that the level of agreement of the rankings from both methods is moderate, while, they both showed poor correlation with crash history. This indicates that there is a need for continuous testing and development of IRSA methodologies since existing ones have a great variation in terms of the choice of parameters such as; risk factors, segmentation approach, risk formulation, and ranking categories. The insights derived from this study are very relevant to road technicians and practitioners involved in road safety assessment procedures.
In 2023, about 1.19 million road users were killed according to the WHO, and the Academic Expert Group (AEG) estimates that approximately one-third of these deaths were work-related. This paper emphasizes that employers are bound to occupational health and safety (OHS) standards while using public roads and should ensure the same attention to traffic injury prevention as in other workplaces. Using analysis of current practices, this paper explores the interplay between road traffic rules and OHS regulations. Work-related driving requires compliance with both road rules and OHS obligations. Organizations often violate road rules, undermining OHS principles that demand that employers take every reasonable step to maximize safety through the use of effective and evidence-based safety measures. This means that work-related traffic should exceed the minimum safety requirements encoded in road rules, and maximize safety through the use of the best available methods. Research shows that several key road safety prevention strategies have demonstrated positive effects, allowing for effective implementation of OHS laws. This paper proposes a 5-point assessment of organizational safety compliance and rigorous safety management based on well-established key safety factors.
Horizontal curves are frequently associated with elevated crash risk because of the combined effects of vehicle speed, roadway geometry, and tire–pavement friction. This study examines these interactions using field data collected from five horizontal curves on NH-340C in India. An empirical model for estimating the maximum available side friction was developed using measured vehicle speeds, superelevation, and pavement surface texture represented by Mean Texture Depth (MTD). Curve safety was evaluated using three complementary indicators: the Safety Index (SI), Change in Safety Index (ΔSI), and Dynamic Curve Safety Index (DCSI), which together describe local stability conditions and safety variations along the curve. The calibrated friction model shows a decrease in available friction with increasing speed and a moderate increase with pavement texture, producing values in the range of 0.16–0.28 that are consistent with international design guidelines. Model reliability was evaluated using uncertainty and sensitivity analysis techniques, including the delta method, bootstrap resampling, the First-Order Reliability Method, and global sensitivity analysis using Sobol and Morris approaches. The results indicate that pavement texture and operating speed are the dominant factors influencing friction variability, while superelevation has a comparatively smaller effect. In addition, a regression-based model was developed to estimate mid-curve operating speeds, which can support the determination of advisory speeds for curve safety management.
The growing integration of in-vehicle centre stack touchscreens has enhanced driver access to information and control systems but raised significant safety concerns due to increased visual distraction. This study investigates whether a short pre-drive training session can mitigate distraction and improve driver interaction with in-vehicle touchscreen. Using a driving simulator and eye-tracking technology, 60 licensed Norwegian drivers were assigned to trained and untrained groups to compare visual attention patterns during secondary tasks involving touchscreen use. Results showed that while all participants exhibited high visual demand on the touchscreen, trained drivers demonstrated slightly lower fixation counts, shorter durations, and reduced self-transition probabilities within the touchscreen area, suggesting more efficient and potentially safer interactions. However, these differences were not statistically significant, indicating a limited effect of the short training provided. The findings highlight the complexity of the touchscreen interface and potential of pre-drive touchscreen familiarization in improving visual attention.
Human factors substantially contribute to road crashes. However, assessing their effects is complex due to the influence of individual characteristics such as personality. Therefore, studies examining the relationship between personality traits and driving behaviour are essential. This study aimed to construct driver behaviour profiles based on these relationships within a large sample of Portuguese drivers. A community sample of 747 licensed drivers, aged under 75 and with at least three years of driving experience, completed an online survey. Instruments included the NEO-Five Factor Inventory-20, the Impulsivity and Sensation Seeking Scale, and the 24-item Driver Behaviour Questionnaire (DBQ). Firstly, multiple linear regressions were conducted considering the three driving behaviour dimensions of the DBQ to support the construction of the profiles. Results indicated that neuroticism, agreeableness, extraversion, impulsivity, and sensation seeking predicted infractions and aggressive driving. Neuroticism, conscientiousness, and impulsivity predicted non-intentional errors, while neuroticism, openness, conscientiousness, and impulsivity were associated with lapses. Even after controlling for age and gender, personality traits remained significant predictors. Secondly, four driver behaviour profiles were constructed using two alternative methodologies: an empirical approach and cluster analysis with k-means. Profiles built using the empirical approach resulted in four groups of drivers characterised by more easily identifiable driving behaviours: prudent, regular, distracted/forgetful, and aggressive drivers. The distracted/forgetful group showed a positive relationship to crash involvement. Overall, the study shows that the complex driver behaviour needs to be carefully grouped.
Walking and cycling are increasingly promoted as sustainable and health-enhancing modes, yet rising volumes in shared urban spaces intensify interactions and perceived conflict potential. While numerous studies show that pedestrian–cyclist interactions rarely result in safety-critical incidents, behavioural adaptations, such as speed reduction and crash avoiding manoeuvres, plays a key role in mitigating risk and increasing perceived safety. As most existing research relies on data-intensive methods such as video observations or simulations, this paper explores the potential of large-scale GPS cycling data to analyse conflict potential and behavioural adaptation in areas shared spaces used by pedestrians and cyclists. Considering the pedestrian zone ‘Prague Street’ in Dresden, Germany, as a case study, we combine GPS trajectories from the 2024th CITY CYCLING campaign with a time-based proxy data for pedestrian density. The results show clear behavioural adaptation: during periods of high pedestrian activity, cyclist do not only use other routes, but cycling volumes decrease and average speeds are reduced by approximately 5–8 km/h. The findings confirm established relationships between density, speed, and conflict mitigation, while highlighting both the opportunities and limitations of GPS based approaches. The study demonstrates that such data can serve as a scalable screening tool for assessing behavioural adaptation and potential risk in shared spaces. We further propose a model considering most relevant data to comprehensively analyse risk potential in near future.
Vertical grades and vertical curvature significantly influence traffic safety. However, obtaining accurate and large-scale data on roadway vertical alignment remains a major challenge. This paper presents a cost-effective and efficient method for estimating roadway vertical alignment using publicly available aerial LiDAR data provided by the United States Geological Survey. An Artificial Neural Network (ANN) model was proposed to predict whether a LiDAR point belongs to a vertical curve or a tangent segment. Due to the limited availability of actual roadway vertical alignment data and the substantial data requirements of machine learning models, a synthetic training dataset was generated by systematically varying road grades and segment lengths to represent realistic combinations of tangents, crest and sag curves. This approach ensured that the model was exposed to a wide range of geometric configurations and allowed it to learn generalized relationships between vertical alignment features and their corresponding geometric parameters. The model was then independently evaluated by comparing the vertical alignment estimated from the extracted aerial LiDAR data for two-lane two-way rural roadways, Route 152 in New Jersey and Route 299 in California, with their corresponding actual vertical alignment data. In addition, a case study was conducted on another rural two-lane highway in which the model was used to compute safe speeds for each roadway segment. The resulting speeds were then compared with the posted speed limits along the corridor. The satisfactory estimation results of this study indicate that the proposed approach can be used for conducting large-scale analyses to estimate vertical alignment using publicly available LiDAR data.
Although approximately 29% of traffic fatalities involve excessive speed, individual vehicle technology that can reduce speeding has not been widely studied or implemented in the United States (U.S). Starting in 2022, NYC DCAS conducted the largest public pilot of active Intelligent Speed Assistance (ISA) in the U.S., with approximately 400 vehicles equipped with a device that prevents acceleration when the vehicle is traveling faster than a preset threshold over the speed limit (typically 11 mph). Using an “opportunity to speed” framework (i.e., only account for driving time when a driver is traveling at least 5 mph below the speed limit), an analysis of 270 vehicles equipped with ISA showed there was a 64.18% relative decrease in the time driven >11 mph over the posted speed limit following ISA activation compared to before activation. This decrease in time spent speeding was not seen in non-equipped control vehicles. Speeding drive time reduction ranged from ~50% on 25 mph local roads, which have speed safety cameras set to the same enforced speed threshold, to 77% reduction on 50 mph roads. In addition, the impact of ISA on speeding behaviour of habitual speeders in 130 vehicles was similar to that on the primary cohort, indicating active ISA is effective at significantly reducing severe speeding across a wide range of drivers and fleets.
This study was motivated by the relatively high number of traffic accidents along Banda Aceh-Medan Highway, where driver fatigue has been repeatedly cited as the key contributing factor. The research aimed to determine the extent to which physical and mental fatigue influence driving speed behaviour on this long-distance route. A quantitative survey was conducted with 400 drivers, both professional and private, using the validated fatigue scales and Structural Equation Modeling for the data analysis. The results indicated that physical fatigue negatively affects speed stability, while mental fatigue significantly increases speed variability. Nevertheless, both physical and mental fatigue explaining 57.8% of the variance in driving speed. These findings highlight the dual cognitive and physiological dimensions of fatigue, emphasizing its role in impaired speed regulation and increased accident risk. This study contributes to existing knowledge by quantifying the distinct effects of physical and mental fatigue on driving performance in a real-world setting, thereby offering empirical support for targeted fatigue management interventions on long-distance routes.
Young novice drivers are overrepresented in crash statistics, highlighting the need for effective training interventions. Swedish authorities have discussed simulator-based screening tests to improve licensing outcomes. This study investigated how visual versus auditory navigation instructions affect driving performance, cognitive load, and user experience in a driving simulator. A highly relevant comparison as the real-world driving tests uses auditive navigation through an examinator. Fifty students at an automotive high school with prior driving simulator experience were assigned to either a visual or auditory instruction group. Participants completed urban driving scenarios with intersections and roundabouts, while metrics such as speed, lane positioning, acceleration/braking, distance to other vehicles, and adherence to traffic rules and instructions were recorded. Cognitive load and user experience were assessed post-drive using NASA-TLX and Likert-scale surveys. Participants receiving auditory instructions committed significantly fewer breaches than those with visual instructions, suggesting there is less driving performance compromise in the auditory navigation condition as compared to the visual navigation condition. No significant difference between groups appeared for cognitive load. These results suggest that auditory instructions better reflect real-world driving test conditions and may enhance the ecological validity of simulator-based screening tests for novice drivers.
Driving education can be challenging for individuals with neurodevelopmental disorders (NDDs) due to the various symptoms which accompanies the disorders. However, previous research on NDDs and driving has prioritized cognitive deficits over specific mitigation strategies for driver training. This study aims to explore driving instructors' experiences of teaching individuals with NDDs with the research questions: (i) what challenges do driving instructors experience when working with individuals with NDDs during the process of teaching and learning to drive? and (ii) how do driving instructors address these challenges in terms of teaching methods and strategies? Thirteen certified Swedish driving instructors with experience teaching students with NDDs participated in semi-structured interviews which were analyzed using qualitative content analysis. The findings reveal both cognitive and structural challenges, for example difficulties processing information in various traffic situations and the need for additional resources. The driving instructors emphasized the importance of clear communication and creating a structured and supportive environment. To meet the needs of learners with NDDs, they described using a range of adaptive strategies. These include breaking down tasks into smaller steps, using repetition, giving clear and concrete instructions, and incorporating illustrations and demonstrations to enhance understanding. The results highlight the importance of targeted, individualized support within driver education for learners with NDDs. They also provide practical insights into current teaching approaches and highlight areas for recommended focus. By shedding light on instructional strategies, this study informs both practice and policy, contributing to a more inclusive, effective and accessible driver education system for individuals with NDDs.
Vulnerable road users (VRUs), such as pedestrians and cyclists, are at high risk in road traffic, accounting for more than half of all global traffic fatalities. Ensuring safe interactions with highly automated vehicles (AVs) requires understanding and predicting VRUs' behaviour. This study investigated the relevance and predictive role of human values alongside environmental factors in real-world VRU-AV interactions. In a field experiment using a Wizard-of-Oz paradigm, 28 pedestrians and 29 cyclists interacted with an oncoming vehicle in a space-sharing scenario. Human values were assessed both qualitatively and quantitatively, while distance to the vehicle and driving mode (AV vs. manually driven) were manipulated. Results show that numerous human values (e.g. comprehensibility, legal compliance, self-efficacy, relaxedness) were rated as highly relevant, but only values related to relaxed interaction significantly predicted pedestrians' behaviour. Distance predicted interaction behaviour for VRU groups, whereas driving mode had no effect. Overall, the findings highlight the importance of considering both environmental factors and human values. The study demonstrates that values provide a broader perspective for understanding VRU behaviour and informing the design of safe, trustworthy, and acceptable VRU-AV interactions.
Fully autonomous Level-4 electric taxis, operating independently without a human driver, are no longer a novelty and are already operating on public roads in the USA and other countries. It is clear that the mobility sector is facing extensive changes, which also affects cities like Zurich. But to what extent will those transport concepts be adopted in cities in the future? Are Level-4 self-driving electric taxis welcome on its streets? This study examined whether this revolution in passenger transport would find acceptance on the streets of Zurich. We explored in which cases, by whom, and for which routes autonomous taxis would be utilized. An online survey with 302 participants assessed the potential intent to use these taxis both during the day and night. The questionnaire was developed based on various theoretical models of technology acceptance and other traffic-related studies and was specifically adapted to the conditions in Zurich. The results showed that factors such as safety and utility evaluations, social influences, and attitudes toward new technologies are significant predictors of usage intention in Zurich. The results also indicate that respondents are not yet fully prepared to hand over control, although the participants expressed an interest in this new technology and an intention to use it. Sociodemographic factors such as age, gender, or education level showed no consistent influence. Based on these findings, several practical implications were identified and subsequently developed, such as highlighting the relevance of safety and user-friendliness in self-driving taxis.
