Journal of Safety Research最新文献

Problem: The surge in popularity of electric kick scooters (e-scooters) poses new challenges for traffic planning, demanding a comprehensive understanding of route choice behavior to see how e-scooters are used, how they affect traffic flow, and where improvements can be made to the road infrastructure. Therefore, this study aimed to analyze route choices and preferences of e-scooter riders and cyclists in a quasi-experimental setup with both user groups having the same trip destinations. Method: Two groups of participants (n = 52) completed a ride with either a shared e-scooter or bicycle to reach four predefined destinations in Dresden, Germany. The riders were supposed to choose their routes and subsequently reported the difficulty of decision-making and the importance of several route choice factors related to the ride. Results: E-scooter riders rated road surface and safety as significantly more important for route choice than cyclists and tended to perceive the decision-making as more difficult. Riding data revealed broad comparability between the groups, with e-scooter riders tendentially having longer routes for complex decisions (unknown destinations, scenic routes, more turns required). Discussion: The study suggests that the route preferences of e-scooter riders may be influenced by a combination of road surface and safety considerations, highlighting the need for high-quality cycling infrastructure. Limitations exist regarding the naturally occurring differences in riding experience in e-scooter riding versus cycling. Practical implications indicate that planning for e-scooter riders can benefit from insights drawn from activities designed for cyclists. The provision of real-time road quality information is proposed, considering its potential impact on overall road safety. Summary: This study contributes to a better understanding of how e-scooter riders navigate through cities and delivers a valuable foundation for transport planners and engineers considering the rise in cycling and micro-mobility use.

Introduction: Despite deployed efforts to establish strict road safety standards, human factors is still the leading cause of road crashes. To identify determinants of driver’s behavior, TPB (Theory of Planned Behavior) is widely used as a prominent theory of behavior change. However, the existence of different aberrant driving behaviors (decision errors, recognition errors, violations, and physical condition related errors) and several studies using TPB to understand driving behavior, makes it important to conduct a literature review and a meta-analysis of existing studies to use their results in effective driving behavior change interventions. Method: The selection process provided 125 relevant studies that were published between 1991 and 2022, and that used TPB for the understanding of aberrant driving behavior. Five fundamental research questions were defined to identify information to be discovered from the literature review and from the meta-analysis. Results: In addition to the standard TPB constructs (attitudes, subjective norms, and perceived behavioral control), past behavior, moral norms, and descriptive norms were used in studies for a more comprehensive understanding of aberrant driving intention. This analysis demonstrated a significant correlation between aberrant driving intentions and past behavior. Also, moral norms construct was correlated with violations and recognition errors, whereas descriptive norms construct was correlated just with recognition errors. Conclusions: The results of this study highlight the strength of TPB in the prediction of aberrant driving intention and its potential effectiveness to guide interventions aimed at changing aberrant driving behaviors. The study contributes to the comprehension of the relevant psychological factors influencing the engagement of drivers in each category of aberrant driving behaviors. Practical Applications: Researchers can use the results of this study to select the relevant psychological factors adapted to their interventions of driving behavior change. The results of the meta-analysis can also be used in the prediction of driver’s intentions.

Introduction: Engagement in hand-held phone use while driving among young drivers is a prevalent concern in society, despite countermeasures to deter the behavior. The social norm approach has been effective in reducing negative behaviors in young adults (e.g., binge drinking, drink driving). However, whether this approach can reduce hand-held phone use while driving in this population has not been thoroughly investigated. Method: The qualitative study explored young drivers’ attitudes and opinions on social norm messages designed to reduce hand-held phone use while driving. In addition, young drivers’ opinions on current campaigns were explored to provide further insight into the effectiveness of these messages. Thirty young drivers were interviewed and shown six social norm messages. Results: The data were analyzed using reflexive thematic analysis, resulting in five themes and one sub-theme: (1) Road safety messages with minimal impact on hand-held phone use while driving; (2) What constitutes an effective road safety message for hand-held phone use while driving; (3) Comparisons between social norm messages and road safety messages; (4) The potential benefits of combined social norms, (4a) Improving and optimizing the message; and (5) “It’s kinda just numbers on a screen”: Negative views on social norm messages. Results highlight the diverse opinions towards road safety campaigns and the need to increase exposure to these messages. Further, a combined social norm message was perceived as most effective in reducing engagement in hand-held phone use while driving. Conclusions: The current study provides preliminary evidence that the social norm approach may be effective in reducing hand-held phone use among young drivers. Further, this study highlights the need to maximize exposure to phone use while driving campaigns in this high-risk cohort. Practical Applications: Results support the development of a social norm messaging intervention to reduce young drivers hand-held phone use while driving.

Introduction: With cycling gaining more popularity in urban areas, it is vital to obtain accurate knowledge of cyclists’ behavior to develop behavioral models that can predict the cyclist’s intent. Most conflicts between cyclists and vehicles happen at crossings where the road users share the path, especially at unsignalized intersections. However, few studies have investigated and modeled the interaction between cyclists and vehicles at unsignalized intersections. Method: A bike simulator experiment was conducted to scrutinize cyclists’ response process as they interacted with a passenger car at an unsignalized intersection. An existing unsignalized intersection in Gothenburg was simulated for test participants. Two independent variables were varied across trials: the difference in time to arrival at the intersection (DTA) and intersection visibility (IV). Subjective and quantitative data were analyzed to model the cyclists’ behavior. Results: When approaching the intersection, cyclists showed a clear sequence of actions (pedaling, braking, and head turning). The distance from the intersection at which cyclists started braking was significantly affected by the two independent variables. It was also found that DTA, looking duration, and pedaling behavior significantly affected cyclists’ decisions to yield. Finally, the questionnaire outputs show that participants missed eye contact or communication with the motorized vehicle. Conclusions: The kinematic interaction between cyclists and vehicles, along with the cyclist’s response process (visual and kinematic), can be utilized to predict cyclists’ yielding decision at intersections. From the infrastructural perspective, enhancing visibility at intersections has the potential to reduce the severity of interactions between cyclists and vehicles. The analysis of the questionnaire emphasizes the significance of visual communication between cyclists and drivers to support the cyclist’s decision-making process when yielding. Practical applications: The models can be used in threat assessment algorithms so that active safety systems and automated vehicles can react safely to the presence of cyclists in conflict scenarios.

Introduction: Previous research has identified the perception of penalties as one of the most important deterrents to road traffic offenses. This study investigated whether the perceived effectiveness and the perceived strictness of penalties for different traffic offenses are associated with prior punishment experience and evaluation perspective (personal – if participants were being punished themselves, vs. general – for punishing all drivers). Method: A convenience sample of 1,374 Lithuanian drivers participated in the survey (56.3% males; aged 18–77 years). Among them, 801 participants had no penalties for traffic offenses, 333 reported monetary fines in the last year, and 240 reported having their drivers license suspended at least once in their driving career. A scale with 10 specific penalties for traffic offenses was developed to measure the perceived effectiveness and strictness of penalties. Half of the participants evaluated the penalties as if they were personally sanctioned for each traffic offense (personal perspective), while the other half assessed the effectiveness and strictness of the penalties for drivers in general. Results: The results indicated that the perceived effectiveness of penalties was related to the evaluation perspective, being higher for changing one’s own behavior than for changing behavior in general. However, the perceived effectiveness of penalties was not related to prior punishment experience. Males and drivers who had experienced their license being suspended reported the highest perceived strictness of the penalties, whereas females and drivers with no prior punishment experience perceived penalties as the least strict. Practical applications: These findings suggest the need for developing new ways of communicating penalties to different groups of drivers. Nevertheless, this research was exploratory in nature and further research is warranted.

Introduction: Pedestrians are a particularly vulnerable group of road users. Mobile phone usage while walking (MPUWW) is a significant contributor to pedestrians’ involvement in road crashes and associated injuries. The current study aims to explore the effect of state mindfulness on daily MPUWW via phone dependence (at the within-person level), and the moderating role of risk perception (at the between-person level) in the phone dependence-MPUWW relationship. Method: We utilized a fine-grained method, the daily diary methodology (DDM) to explore the aforementioned model. A total of 88 Chinese college students participated in a consecutive 12-day study, yielding 632 daily data. Unconflated multilevel modeling was used to analyze the data. Results: After trait mindfulness being controlled, state mindfulness has a negative impact on MPUWW via phone dependence at the daily level. Furthermore, risk perception as an individual difference variable moderates the relationship between phone dependence and MPUWW, in which a weaker effect observed in individuals with higher levels of risk perception. Conclusions: State mindfulness can decrease the frequency of daily MPUWW by reducing phone dependence, and risk perception is a crucial factor in mitigating the negative effects of phone dependence on MPUWW. Practical applications: To lower MPUWW and thereby minimize the risk of road crashes and associated injuries, it is beneficial to foster present-moment awareness of individuals, encourage individuals to use mobile phones in a balanced and sensible manner, and integrate the enhancement of risk perception into road safety education.

Introduction: An on-road study was conducted to examine the effects of level 2 automation on the stressfulness and enjoyment of driving and driving attention following prolonged usage. The study also examined the changes in the automated driving experience and attention over time as well as important predictors such as pre-driving trust in technology and attitudes toward automated systems. Method: Motorists who had never used automated systems drove a level 2 automation vehicle for a 6–8 week period. Results: Participants reported that the automated systems reduced the stress of driving and made traveling more enjoyable and relaxing. They also reported that the automation did not make traveling boring and take the fun out of driving. Participants indicated that their minds tended to wander when the automation was operating. The stressfulness of the automated driving experience decreased over time. Participants also reported feeling increasingly comfortable driving with the automation without monitoring it closely. The enjoyment and stress of automated driving is important because it shapes the willingness to use the automation and, hence, the safeness of driving. As expected, intentions to use and purchase automated systems were strongly predicted by the perceived favorableness of driving with the automation. Participants’ pre-driving beliefs about automated systems, rather than their trust, appears to have shaped their experiences with the automation. Practical Applications: Although some of the findings suggest that automated systems increase unsafe behavior by novice users, other facets of the surveys suggest that motorists are cognizant of the risks of automated driving and discreet in their usage of the automation.

Introduction: This study presents a comprehensive analysis of wrong-way driving (WWD) fatal crashes on divided highways in the United States over a 17-year period, from 2004 to 2020. The study aims to uncover trends, distribution patterns, and factors contributing to these fatal crashes. Data were extracted from the National Highway Traffic Safety Administration (NHTSA) Fatality Analysis Reporting System (FARS) database. Methods: Descriptive statistical analysis was used to reveal general crash characteristics, while trends were updated through an examination of the annual occurrence of WWD fatal crashes. The study further employed binomial logistic regression to compute odds ratios, identifying significant contributing factors. These factors encompassed temporal variables, crash characteristics, and driver characteristics. The odds ratios shed light on the relationship between WWD fatal crashes and other fatal crashes, allowing for the identification of key elements that drive WWD incidents. Results: On average, 302 WWD fatal crashes occurred annually, resulting in 6,953 fatalities during the study period. The frequency of WWD fatal crashes remained relatively stable, with a slight increase over time. According to the model, variables include day of week, time of day, month, lighting conditions, weather conditions, roadway profile, collision type, passenger presence, driver age, gender, license status, and driver injury severity were found to significantly impact the occurrence of WWD fatal crashes. One significant finding is that road profiles like sag curves or hillcrests can increase the likelihood of WWD fatal crashes. Practical Application: The findings of this study contribute to an improved understanding of WWD fatal crashes on divided highways, thereby aiding in the development of strategies for prevention and mitigation.

Introduction

To the authors’ knowledge, no systematic review has examined the definition of safety leadership in the academic literature to date. A review was therefore carried out to determine how safety leadership was defined in the peer reviewed empirical literature and thematic analysis was employed to identify patterned meanings across the data.

Method

Thirty-seven primary definitions, or definitions that were not borrowed from other studies, were identified. Of these 37, seven conceptual definitions were found to be evidence-based, six of which were endorsed by their operational counterpart definitions and one which was derived using exploratory research.

Results

These seven definitions showed strong alignment with the three themes that emerged from the thematic analysis that capture the why, how, and who of safety leadership. Transformational leadership theory formed the foundation for many of the definitions in the academic literature, despite recent evidence suggesting that adopting multiple forms of leadership styles would be more effective for improving workplace safety.

Practical Applications

Gaps in the current evidence base are explored and suggestions for future research are discussed.

Introduction: Industry 4.0 has brought new paradigms to businesses based on high levels of automation and interconnectivity and the use of technologies. This new context has an impact on the work environment and workers. Nevertheless, these impacts are still inconclusive and controversial, requiring new investigative perspectives. This study aimed to investigate the requirements sought, the risk factors identified, and the adverse effects on workers caused by the characteristics of I4.0. Method: The methodology was based on a systematic literature review utilizing the PRISMA protocol, and 30 articles were found eligible. A descriptive and bibliometric analysis of these studies was performed. Results: The results identified the main topics that emerged and have implications for workers' Occupational Health and Safety (OHS) and divided them into categories. The requirements are related mainly to cognitive, organizational, and technological demands. The most significant risk factors generated were associated with the psychosocial ones, but organizational, technological, and occupational factors were also identified. The adverse effects cited were categorized as psychic, cognitive, physical, and organizational; stress was the most cited effect. An explanatory theoretical model of interaction was proposed to represent the pathway of causal relations between the requirements and risk factors for the effects caused by I4.0. Conclusions and practical applications: This review has found just how complex the relationships between the principles of Industry 4.0 are (e.g., requirements, risk factors, and effects) and the human factors. It also suggests a pathway for how these relationships occur, bridging the gap left by the limited studies focused on connecting these topics. These results can help organizational managers understand the impacts of I4.0 on workers' safety and health.