BackgroundActive transportation (AT) marks an eco-friendly mode of physical activity that is well integrable into daily life. Despite the dominance of social-ecological approaches to explaining AT, previous studies often drew on a fragmented set of variables to describe AT behavior. The concept of physical literacy (PL) comprises physical, affective, and cognitive determinants for physical activity and, therefore, enables a concentrated, theory-guided view on intraindividual determinants for AT. The goal of the present study was to examine empirical associations between PL and modes of AT (considering the influencing and moderating effect of grade and sex/gender, respectively). MethodsWithin the scope of the DAPL study, data from 663 children (age: 6–13 years) from 41 classes (grades 1–6) across twelve schools in Denmark were analyzed. The school children (mean age: 9.81 years; 55 % girls) completed measurements of PL (Danish version of the CAPL-2: physical, affective, and cognitive component; total score) and self-reported their AT mode for seven days. We calculated general mixed models with the class as a random-effects factor to examine the relationship between PL and six different modes of AT. ResultsTotal PL as well the physical, cognitive, and affective domains of PL were not associated with overall AT (p > 0.05). However, we found significant associations of total PL (B = 0.35) and the physical domain (B = 0.21) with biking. The affective and cognitive domains of PL did not significantly correlate with any AT indicator. The present effects were not moderated by students’ grade and sex/gender. ConclusionsPublic health strategies should strive for a mode-tailored approach when targeting children’s AT. Person-centered health and physical education must increase their efforts in promoting children’s holistic biking skills to effectively foster AT behavior. The provision of holistic experiences should emphasize the integration of psychomotor and affective learning.

Mobility as a Service (MaaS) is a transformative approach to urban mobility that offers a convenient, sustainable, and user-centered transportation experience. Despite its recent investigations, service experience and satisfaction of MaaS remain less research attention. This study empirically investigates the effects of service quality on MaaS satisfaction. Using a sample of 459 MaaS users in Kaohsiung, Taiwan, the structural equation modeling (SEM) analysis results reveal that dimensions of service experience, including physical effort, affective effort, seamlessness, experiential value, and autonomy/competence significantly influence user satisfaction. To explore the unobserved heterogeneity among MaaS users, the finite mixture modeling (FIMIX) segmentation results reveal our latent groups: value-conscious, convenience-conscious, planning-conscious, and uncertainty-averse users. The necessary condition analysis results show that seamlessness and experience value are necessary conditions for MaaS user satisfaction. Empirical implications for a user-centered MaaS are made.

As automated vehicles continue to advance, teleoperation has emerged as a critical support system for navigating complex and unpredictable environments that exceed the vehicles' current autonomous capabilities. A main issue in the implementation of teleoperation is latency caused by the high bandwidth required to transmit the video feed from the vehicle to the remote teleoperation station. A possible approach for addressing the latency problem is the transfer of lower-resolution or compressed videos between the vehicle and the teleoperation station. When applying semantic segmentation on the video feed, many pixels are mapped to a limited set of possible colors according to the types of objects that they represent. This concept has been commonly used in autonomous driving algorithms and has the potential to enable the transferring of smaller-sized videos thus reducing bandwidth. In this study, we examine how presenting semantically segmented driving scenes to humans affects their perception of the scene, and specifically, how it affects their hazard perception and situation awareness. We conducted two user studies comparing the effects of using different levels and types of semantic segmentation. Our results indicate that viewing partly segmented scenes, such that only a selected set of object types are colored, commonly achieves the same effect, and sometimes even outperforms a realistic view. Our study and its insights may pave the way for future research, development, and design of teleoperation systems of automated vehicles.

The Dunning-Kruger Effect (DKE), a widely recognized phenomenon, reveals that individuals with lower skills tend to overrate their abilities, while high achievers often underestimate themselves. This intriguing trend has been explored in the realm of car driving using an innovative, purpose-built methodology. This methodology integrates visual presentations of specific driving scenarios for self-assessment alongside the analysis of actual driving behaviours gathered through driving simulation. Our study recruited both inexperienced, non-drivers and seasoned, licensed drivers to delve into three key aspects: (i) explore how the acquisition of skills through extensive real-world experience influences the DKE pattern, (ii) refine the process of recalibrating self-assessed skills subsequent to a brief encounter with the tasks and (iii) determine how the DKE is affected by varying degrees of cognitive control required to execute diverse driving tasks. The data consistently confirms the DKE across driving situations, highlighting its universality. Novice and seasoned drivers both display the pattern before and after the simulated drive, regardless of the associated level of cognitive control, indicating that experienced drivers are prone to the same misestimation tendencies as novices. Novices’ self-assessments notably increased after experiencing the simulated drive, while experienced drivers’ estimations remained stable. This observation could be interpreted as the dual curse of ignorance at work. This research offers valuable insights into the dynamics of self-assessment over time, shedding light on how driving experience and task exposure impact individuals’ perceptions of their own abilities.

Drunk driving is a worldwide road safety concern that has led to road crashes. In Iran, while the production, distribution, and consumption of alcohol are prohibited, drinking has increased significantly over the last decade, resulting in a corresponding rise in drunk driving and related crashes. Therefore, this study adopted a mixed methods approach aimed at evaluating the factors influencing young drivers’ intentions to drink and drive, along with the facilitators and barriers to this behavior. Quantitative data was collected from 537 drivers aged between 18 and 25 with valid driving license in Tehran, Iran. An extended theory of planned behavior (TPB) model was proposed, and structural equation modeling was used to evaluate the proposed model. Qualitative data was collected via semi-structured interviews with 33 young drivers who had engaged in drunk driving at least once in the past six months, and reflective thematic analysis was used to analyze the data. The findings of the survey highlighted the prevalence of drunk driving among young drivers, as 24.4% of participants reported driving under the influence of alcohol at least once in the past six months. The results showed that perceived risk, perceived behavioral control, attitudes, descriptive norms, and perceived ability to manipulate enforcement were significant predictors of intentions to drink and drive. The results of the interviews revealed that participants considered the social and cultural context of the country as the basis for the facilitators and barriers of drunk driving, subsequently forming their future behavior. Social restrictions for drinking and lack of education and specific legislation were mentioned as the facilitators, while legal and non-legal sanctions were considered as important barriers. The findings of this study provided an understanding of the underlying constructs of drunk driving to provide effective policy and practical implications that can be developed to address the issue.

Alcohol and drugs, including Tetrahydrocannabinol (THC), significantly impact roadway safety by impairing cognitive functions, coordination, and reaction times, leading to increased crash risk and severity. This study examines the prevalence of alcohol and drugs among 4,586 injured roadway users (drivers, riders, and passengers) in the U.S. from 2019 to 2021, utilizing an XGBoost model to identify key variables associated with Injury Severity Score (ISS) in substance-related traffic crashes, and highlighting influential factors such as injury location, demographic characteristics (age, race), safety compliance, and alcohol and drug presence. These risk factors were further analyzed through Cluster Correspondence Analysis (CCA) to reveal patterns and trends affecting injury severity across different demographic and behavioral groups. The findings reveal that 55.8% of the injured tested positive for substances, with cannabinoids being the most common, followed by alcohol, stimulants, and opioids. This study identified six core crash clusters, each with distinct characteristics, including older drivers, impaired young drivers, specific driver ethnicities, and motorcyclists. Key findings from clusters indicate that older drivers, despite high safety compliance and negative substance tests, faced crash risks potentially due to age-related limitations. Impaired young adult crashes arecharacterized by risky behavior, including alcohol and THC use combined with low safety compliance, while motorcyclists with high substance involvement and inconsistent helmet use, are identified as a high-risk group, frequently experiencing severe leg injuries. These insights underscore the need for comprehensive traffic safety policies targeting substance use and promoting effective safety measures to mitigate crash risks and improve road safety.

Pedestrian violations are among the biggest concerns for administration as they contribute to increased frequency and severity of pedestrian-related crashes. Typically for ensuring pedestrian safety, law enforcement measures such as pedestrian penalties are used. To assess the efficacy of such enforcements, pedestrian sentiments towards these law enforcements need to be determined. There is a general lack of studies assessing the effect of pedestrian law enforcement on pedestrians’ behavior. Using Qatar based data, this study assessed the effectiveness of a recent law amendment in State of Qatar to improve pedestrians’ behavioral intentions. Based on 645 survey responses, a Partial Least Squares Structural Equation Modelling (PLS-SEM) approach was used to verify quantitative relationships among law amendment, risk perception, safety effectiveness perception, and pedestrians’ behavioral intentions. The results indicate that the pedestrians’ behavioral intentions are strongly influenced by law emphasis, risk perception, and safety effectiveness perception. Moderating role of respondent attributes such as their demographics, personal experiences of respondents with traffic issues, and experience regarding law enforcement are also determined. The structural path between risk perception and behavioral intentions was significantly moderated by gender and jaywalk frequency. Further, nationality and education showed moderating effects on structural path between behavioral intentions and law effectiveness and safety effectiveness perception. Findings from this study contribute to the theoretical understanding of pedestrians’ behavior and can be used for planning and implementation of targeted law enforcement to improve pedestrian safety.

Car-following behavior is the most fundamental and common driving behavior and is crucial for road safety and traffic efficiency. Traffic flow dynamics are greatly affected by this behavior, and driver-related factors in car-following behavior have been identified as a key cause of rear-end crashes. Despite extensive research on car-following behavior, a gap remains in understanding how this behavior manifests itself in culturally diverse driver populations and heterogeneous driving conditions. The aim of this study was to empirically investigate the effects of individual characteristics, leading vehicle types, posted speed limits and deceleration rates of the leading vehicle on car-following behavior. To this end, the car-following behavior of 61 participants was investigated in eight different scenarios involving a motorbike, sedan, SUV, and truck as the leading vehicle under two different speed limits, i.e., 50 km/h and 80 km/h in a driving simulator environment. The results showed that considerable variations in car-following behaviors exist depending on gender, age, driving experience, educational levels, and the type of leading vehicle, as well as speed limits and deceleration rates. The risk of rear-end crash was found to be higher at the lower speed limit and with a two-wheeler (motorbike) as the leading vehicle. Additionally, females were identified as a having higher crash risk than males. In summary, this study provides valuable insights that could be applied to enhance road safety, such as tailoring targeted training materials for high-risk groups and informing policy decisions. Incorporating these insights into model calibration can lead to more accurate and realistic simulations that capture the complexities of real-world driving scenarios.

Road crash injuries have emerged as a significant public health issue in many low-and middle-income countries in recent years. Annually, more than 1.35 million people lose their lives due to road crashes, making it one of the leading causes of death worldwide. In India, road crash injuries have increasingly become a major concern for motorized two-wheeler riders. It is important to understand risky riding behaviours to develop accurate and evidence-based risk reduction programmes that fit the target population well. The current study aimed to identify the psychosocial determinants of refraining from risky riding behaviour in young, motorized two-wheeler riders. A quantitative survey based on the theory of planned behaviour (TPB) complemented with questions measuring routine behaviours was conducted among 238 young riders aged 18–25 riding motorized two-wheelers in Manipal, a locality of Udupi district in Karnataka province of Southwestern India. The study tool assessed four risky riding behaviours: (1) speeding, (2) helmet non-use, (3) performing stunts, and (4) using mobile phones while riding. The results of the study indicated that the intention to refrain from risky riding behaviours can be explained by important psychosocial determinants of human behaviour, including attitude, social norms, and perceived behavioural control and their underlying belief systems with regard to perceived benefits and costs, perceptions of other’s behaviours and approval, and expressions of personal control that inform these psychosocial determinants. In addition, the extent to which participants automatically behaved in risky riding practices in the past did not prove to be a strong predictor of future intentions to refrain from risky riding. It is concluded that the study resulted in an in-depth understanding of the psychosocial determinants of risky riding behaviour. Policymakers and programme developers are encouraged to use the findings in defining programme goals for future educational interventions to promote safe two-wheeler riding.

The use of situation awareness (SA) measures to assess relative safety in driving is common, with higher levels of SA being interpreted as safer. These relative interpretations do not allow researchers to determine whether the level of SA could be considered “safe” or “unsafe”. In contrast to such interpretations based on relative performance, the current position paper explores the potential for a normative interpretation of situation awareness with regard to safety assessment in driving. A series of expert interviews yielded viewpoints on the current relation between SA and safe driving, theoretical underpinnings for a normative approach, and potential actions towards an SA criterion for safe or unsafe driving. Methodological challenges regarding a normative approach are discussed together with considerations towards a weighted criterion-based approach to SA. The selection of SA requirements relevant for safety and the differentiation and weighting of these requirements on high and lower importance is presented. A method towards objective determination of relevance and weight of SA requirements may increase the usefulness of SA measures for assessment of safety in a driving context.