Crash risk and aberrant driving behaviors among bus drivers: the role of personality and attitudes towards traffic safety

Examining the injury severity of public bus-taxi crashes: a random parameters logistic model with heterogeneity in means approach

Public buses and taxis play crucial roles in urban transportation. Ensuring their safety is of paramount importance to develop sustainable communities. This study investigated the significant factors contributing to the injury severity of bus-taxi crashes, using the crash data recorded by the police in Hong Kong from 2009 to 2019. To account for the unobserved heterogeneity, the random parameters logistic model with heterogeneity in means was elaborately developed. The results revealed that taxi driver age, bus age, traffic congestion, and taxi driver behavior had significantly heterogeneous effects on the injury severity of bus-taxi crashes and that the mean value of the random parameter for severe traffic congestion was likely to increase if the taxi's age was <5 years. Taxi driver gender, rainfall, time of day, crash location, bus driver behavior, and collision type were found to significantly affect the bus-taxi crash severity. Specifically, female taxi drivers, old taxis, rainfall, midnight, improper manipulation of bus and taxi drivers, head-on and sideswipe collision types, and non-intersections were associated with a higher likelihood of fatal and severe crashes. Based on our findings, targeted countermeasures were proposed to mitigate the injury severity of bus-taxi crashes.

Correcting for endogeneity of crash type in crash injury severity at highway ramp areas

Crash type, a key contributory factor of crash injury severity level, is typically included in crash severity models as an explanatory variable. However, certain unobserved factors could influence both the crash type and crash injury severity simultaneously. As such, there could exist an endogenous effect of crash type on crash injury severity. The present paper investigates this hypothesis using data from highway ramp areas. These locations tend to be crash-prone because of the frequent lane changes and speed differentials associated with merging, diverging, and weaving of vehicles at those locations. Conventional approaches used in past ramp safety studies modeled crash type and crash injury severity separately, not addressing the endogenous effect of crash type on crash severity at these locations. In this study, a random parameter recursive bivariate probit model is proposed to model the crash type (hit-object and rollover) and crash injury severity at ramp areas simultaneously and to account for any endogenous effect of crash type. The study used highway crash data from ramp areas at highway located in North Carolina from 2016 to 2018. The results indicate that the proposed model can and does capture the endogenous effect of crash type. The likelihood of injury for a rollover crash would be underestimated if endogeneity were not considered. Other exogenous variables including aberrant driving behavior, safety belt, road surface condition, lighting condition, area type, crash location, and ramp type that affect the type and injury severity of crashes at highway ramp areas were identified. The exogenous variables that are significant only for the crash type, such as vehicle type, and speed limit, were detected to have indirect effects on the crash injury severity. Furthermore, the effects of individual heterogeneity of the explanatory variables are considered. Female drivers and old drivers are statistically significant in the means of random parameters. The findings shed light on the potential need and effectiveness of prospective traffic management and control measures to mitigate crash risk at highway ramp areas.

An investigation into the role of driver characteristics in driving behaviours and subsequent clustering of Indian bus drivers

OBJECTIVES

Aberrant driving behaviours among bus drivers cause serious concerns to safety on the road. The present study aimed to measure the effects of driver characteristics on aberrant and positive driving behaviours among bus drivers and to group drivers accordingly. The study was carried out among bus drivers of the government-owned road transport corporation in Kerala, India.

METHODS

A total of 1120 drivers took part in the survey, out of which 617 drivers returned the forms with all questions answered (response rate = 55.1%). SPSS version 27.0 was used for analysis.

RESULTS

Structural equation modelling proved the predictive nature of driver characteristics on driving behaviours. K-means cluster analysis revealed clusters such as violating and angry drivers (cluster 1), knowledgeable drivers with positive driving behaviours (cluster 2), healthy and stress-free drivers (cluster 3), erroneous and stressed drivers (cluster 4) and calm drivers with positive driving behaviours (cluster 5).

CONCLUSION

Positive relationships of anger and stress on aberrant driving behaviours and higher number of drivers in clusters 1 and 4 reveal concerns of safety. The study points towards the necessity of organizational commitment for improving driver characteristics for better driver behaviours and safer roads.

Pedestrian behavior among Chinese seniors: Insights from factor analysis and structural equation modeling

Pedestrians contribute significantly to the total number of road fatalities and injuries, with their behavior playing a pivotal role in traffic mishaps. Despite this, a limited body of research has delved into the walking behaviors of Chinese seniors. Given this gap, our study rigorously examines the patterns of seniors' walking behaviors and their influencing factors. We employed exploratory factor analysis to decipher the intrinsic component structures of seniors' walking patterns in China. Subsequently, structural equation modeling was utilized to analyze the impact of demographic attributes and personality characteristics on these behaviors. The findings revealed a four-dimensional structure for senior walking behaviors: transgression, inattention, aggression, and positive behaviors. Introducing personality traits as variables notably enhanced the explanatory power of our model. Specifically, anger, altruism, and normlessness significantly influenced certain dimensions of walking behaviors, while sensation-seeking did not exhibit any notable effect. This study not only highlights the complexity and diversity of elderly walking behaviors but also underscores the importance of tailored interventions to improve walking safety and quality of life for seniors.

Analyzing the Prevalence of and Factors Associated with Road Traffic Crashes (RTCs) among Motorcyclists in Bangladesh

Methods

A cross-sectional survey was conducted using a structured questionnaire involving 402 motorcyclists from four major southeastern towns, comprising 350 (86.07%) males and 52 (12.93%) females. The chi-square test was applied in bivariate analysis, and binary multivariable logistic regression was performed to determine the risk factors of road traffic crashes.

Results

This study's findings revealed that the overall reported prevalence of road traffic crashes involving motorcycle drivers over one year was 68.66%. Multivariable logistic regression analysis revealed several factors that significantly impacted road traffic crashes. These factors included driving without a valid driving license, the young age (<20) of motorcyclists, driving in rainy weather, exceeding the speed limit, per-week working hours, smoking status, motorcycle ownership, the brand of motorcycle, and not wearing a helmet while driving.

Conclusion

The study findings highlight the need for improving motorcycle safety by implementing measures such as imposing per-week work hour limits for riders, enforcing traffic regulations, and promoting helmet use among motorcycle drivers. The results of this study draw attention to the Bangladesh Road Transport Authority (BRTA) and motorcycle drivers in the country to decrease motorcycle crashes and the severity of injuries by implementing efficient guidelines and strategies for driving motorcycles. The findings of this study can assist policymakers and concerned authorities in taking the essential steps to lessen road traffic crashes among motorcyclists in Bangladesh.

Behind the wheel: Probing into personality, skills, and driving behavior's role in bus rapid transit crashes

OBJECTIVE

Personality traits and driving skills are significantly associated with driving behaviors and crashes. In the case of professional bus drivers, the relationships amongst these variables have not been sufficiently examined in terms of road crashes. Therefore, this study seeks to examine the relationship between personality traits, driving skills, driving behaviors, and crash involvement among Bus Rapid Transit (BRT) drivers.

METHODS

The study employed a comprehensive data collection strategy involving self-reported questionnaires, including the driver behavior questionnaire, driver skill inventory, and Big Five inventory, alongside Global Positioning System (GPS)-extracted speeding data from a sample of 166 drivers. To explore the relationship between variables, the study utilized the Partial Least Squares Structural Equation Model (PLS-SEM) as the analytical method.

RESULT

The findings reveal that self-reported violations and actual speeding performed by drivers were positively associated with crash involvement, whereas positive driving behavior negatively influences violation, errors, speeding and crash involvement. The study also found that the safety skills were negatively associated with violations, errors, and speeding, while higher perceptual-motor skills were associated with higher instances of speeding violations, resulting to a higher possibility of getting involved in a crash. Finally, the study reveals that certain personality traits (extraversion and neuroticism) were positively associated with violations, errors, and speeding, leading to a higher risk of getting involved in crashes, whereas certain personality traits (conscientiousness and agreeableness) were associated with safe driving.

CONCLUSION

The study findings offer valuable insights into the predictors of crashes among professional BRT drivers, which can be used to enhance driving practices, ensuring the safety of the public. Moreover, these findings provide transportation agencies with better management and decision-making capabilities to implement effective interventions to improve road safety.

Unveiling pre-crash driving behavior common features based upon behavior entropy

Driving behavior is considered as the primary crash influencing factor, whereas studies claimed that over 90% crashes were attributed by behavior features. Therefore, unveil pre-crash driving behavior features is of great importance for crash prevention. Previous studies have established the correlations between features such as vehicle speed, speed variability, and the probability of crash occurrences, but these analyses have concluded inconsistent results. This is due to the varying operating characteristics among roadway facilities, where given the same driving behavior statistical features, the corresponding traffic states are not identical. In this study, a behavioral entropy index was proposed to address the abovementioned issue. First, through comparing the individual driving behavior with the group distribution, behavioral entropy index was calculated to quantify the abnormality of driving behavior. Then, crash classification models were established by comparing the behavioral entropy prior to crash events and normal driving conditions. The empirical analyses have been conducted based on 1,634,770 naturalistic driving trajectories and 1027 crash events. And models have been carried out for urban roadway sections, urban intersections, and highway sections separately. The results showed that utilizing the behavior entropy instead of the statistical features could enhance the crash classification accuracy by 11.3%. And common pre-crash features of increased behavioral entropy were identified. Moreover, the speed coefficient of variation (QCV) entropy was concluded as the most influencing factor, which can be used for real-time driving risk monitoring and enables individual-level hazard mitigation.

Personality, perceptions and behavior: A study of speeding amongst drivers in Victoria, Australia

INTRODUCTION

Road crashes present a serious public health issue. Many people are seriously or fatally injured every year in avoidable crashes. While these crashes can have multiple contributing factors, including road design and condition, vehicle design and condition, the environment and human error, the performance of illegal driving behavior, including speeding, may also play a role. The current study aimed to examine the mediating influence that four potential deterrents (perceptions towards enforcement, crash risk, social norms and disapproval, and negative personal/emotional affect) have between the Big Five personality traits (conscientiousness; extraversion; agreeableness; neuroticism; openness) and expectations to speed.

METHODS

A total of 5,108 drivers in Victoria, Australia completed an online survey in 2019. A mediated regression analysis was used to examine pathways in a conceptual model developed for the study.

RESULTS

The results showed that perceptions towards the four potential deterrents examined did mediate the relationship (either completely or partially) between personality and expectations to speed.

CONCLUSIONS

The results of this study suggest that if interventions to deter illegal driving behavior are to be successful, one factor that could be taken into account is the personality traits of drivers who may be at greatest risk of the performance of illegal driving behaviors.

Sensation seeking predicts risky driving behavior: The mediating role of difficulties in emotion regulation

The purpose of this study was to explore the mediating effect of difficulties in emotion regulation on the relationship between sensation seeking and driving behavior based on the dual-process model of aberrant driving behavior. A sample of 299 drivers in China completed the Difficulties in Emotion Regulation Scale, the Driver Behavior Questionnaire, and the Sensation Seeking Scale V (SSS). The relationships among sensation seeking, difficulties in emotion regulation, and driving behavior were investigated using pathway analysis. The results showed that (1) disinhibition and boredom susceptibility are positively and significantly related to difficulties in emotion regulation and risky driving behaviors; (2) difficulties in emotion regulation are positively and significantly associated with risky driving behaviors; (3) difficulties in emotion regulation mediate the effect of sensation seeking on driving behaviors, supporting the dual-process model of driving behavior; and (4) professional drivers score higher in terms of difficulties in emotion regulation and risky driving behaviors than nonprofessional drivers. The findings of this study could provide valuable insights into the selection of suitable drivers and the development of certain programs that benefit road safety.

Task and Resting-State Functional Connectivity Predict Driving Violations

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

Examining the associations between urban bus drivers' rule violations and crash frequency using observational data

Urban bus crashes have been an increasing concern in China thanks to the expansion of urban bus systems. Bus drivers' rule violation behavior appears to be an important factor of bus crashes. However, existing studies rely heavily on questionnaire survey of rule violation behaviors, which may suffer from self-reporting bias. Using observational data of 1,356 bus drivers from onboard video recordings, this paper develops a random parameter zero-inflated Poisson model (with heterogeneity in means and variances) to uncover the relationship between drivers' rule violation behaviors and bus crashes. Model results show that rule violation behaviors such as using a cell phone, driving outside the bus lane, and touching solid line with wheel while driving significantly correlate with crash frequencies with large marginal effects, whereas some other violation behaviors (e.g., running red lights, changing lanes suddenly) show a minor role. This finding highlights the importance of differentiating various rule violations when examining bus crashes instead of aggregating them altogether. Furthermore, the effects of rule violation behavior show substantial heterogeneity. For example, the association between not yielding to pedestrians and bus crashes is enhanced when drivers also show records of touching solid line with wheel while driving, driving outside the bus lane, or are internally trained. Findings of this study provide insights for countermeasures to improve bus safety by targeting critical bus driver groups with specific rule violations, and inform future research to collect observational data on drivers' rule violation behaviors.

Do ride-hailing drivers' psychological behaviors influence operational performance?

Purpose

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

Design/methodology/approach

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Findings

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

Practical implications

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

Originality/value

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

Effects of personality traits on bus drivers' prosocial and aggressive behaviours: The moderated mediating role of risk perception and gender

PURPOSE

The present study aimed to examine the effects of personality traits on bus drivers' self-reported prosocial and aggressive driving behaviours as well as the mediating role of risk perception and the moderating role of gender in this relationship.

METHODS

Three hundred and ten bus drivers who were 24-57 years old agreed to participate in this study. The measures utilized included personality scales, a risk perception scale and a prosocial and aggressive driving behaviour scale.

RESULTS

A moderated mediation model was established. The effects of normlessness/anger on prosocial driving behaviour are mediated by risk perception. Risk perception has a stronger promoting effect on the prosocial driving behaviour of male drivers (b = 0.358, p < 0.01) than it does on that of female drivers (b = 0.072, p > 0.05). The effects of normlessness/anger on the aggressive driving behaviour of both male and female drivers are also mediated by risk perception. Moreover, gender plays a moderating role in the influences of personality and risk perception on aggressive driving behaviour. Drivers with higher risk perception and less anger exhibit less aggressive driving behaviour, and this effect is clearer among male drivers than it is among female drivers.

CONCLUSION

The present study revealed the relationship between personality traits and the prosocial and aggressive driving behaviours of bus drivers through a moderated mediation model. These findings highlight the importance of taking risk perception and gender into consideration when examining the effects of personality on bus drivers' driving behaviours.

The Predictors of Unsafe Behaviors among Nuclear Power Plant Workers: An Investigation Integrating Personality, Cognitive and Attitudinal Factors

Unsafe behaviors, such as violations and human errors, have long been recognized as the main causes of accidents in nuclear power plants (NPPs). However, personal factors that influence unsafe behaviors among NPP workers have not been well examined, especially in an integrated model. This study proposes an integrated contextual mediated model to examine personality, cognitive and attitudinal predictors of unsafe behaviors among commissioning workers at NPPs. The model was verified using structural equation modeling technique with survey data from 177 commissioning workers in two Chinese NPPs. Results show that personality traits (i.e., conscientiousness, neuroticism, openness and agreeableness), executive function and safety attitudes exerted significant effects on unsafe behaviors. In addition, the effects of agreeableness and executive function were partly mediated by safety attitudes. Both conscientiousness and neuroticism indirectly influenced unsafe behaviors through the mediating role of executive function. The findings shed light on the design of evidence-based interventions for safety performance in NPPs.

Applying systems thinking to improve the safety of work-related drivers: A systematic review of the literature

INTRODUCTION

Light vehicles (<4.5 tons) driven for work purposes represent a significant proportion of the registered motor vehicles on our roads. Drivers of these vehicles have significant exposure to the dangers of the road transport environment. To optimize safety for these workers, it is critical to understand the factors contributing to risk of being involved in an incident. This information can then be used to inform the review and revision of existing risk controls and the development of targeted prevention activities.

METHOD

The aim of the study was to undertake a systematic review of the literature to identify the factors associated with work-related driving incidents. The factors identified in the review were represented within an adapted version of Rasmussen's risk management framework (Rasmussen, 1997). Fifty studies were analyzed following data screening and review of full text. The highest proportion of risk factors were categorized at the lower levels of the system, including the 'Drivers and Other Road Users' level (n = 20, 44.4%) and the 'Equipment, Environment, and Meteorological Surroundings' level (n = 19, 42.2%). There were no risk factors identified at the 'Regulatory and Government Bodies' levels of the framework, confirming the narrow investigative scope of past research and the need to acknowledge a broader range of factors within and across higher levels of the system.

CONCLUSIONS

The findings of this study inform the direction of future research and design of targeted prevention activities capable of creating system change for the safety of work-related drivers.

A quantitative traffic performance comparison study of bicycles and E-bikes at the non-signalized intersections: Evidence from survey data

As common transportation modes at non-signalized intersections, bicycles and e-bikes have been involved in most traffic crashes. Although a large number of studies have been dedicated to studying the safety problems caused by bicycles and e-bikes, there is still limited attention paid to the differences between them, especially at non-signalized intersections. This paper compares the differences between bicycles and e-bikes based on a self-administered questionnaire. This questionnaire was distributed to bicycle users (N = 453) and e-bike users (N = 439). The personal characteristics, decision-making capacity, the feeling of infrastructure, perceived level of service, and perceived level of risk were adopted as the performance indicators to depict the difference in the study area. Using statistical methodologies and the Structural Equation Model (SEM), key findings indicate that perceived level of service was found to be significantly different between bicycles and e-bikes at most non-signalized intersections. 43.4 % of e-bike riders often or always choose to avoid riding under extreme weather, while 58.7 % of bicycle riders avoid riding under extreme weather. Moreover, compared with bicycles, e-bikes' decision-making capacity is affected more by infrastructure quality. The difference between bicycles and e-bikes highlights the need for differentiated development of cycling safety education and law enforcement.

Exploring the Knowledge and Attitude of the Taxi Drivers in the Field of Traffic Rules and Regulations

Background. In all countries, the knowledge of driving guidelines is the most important and critical mechanism to ensure the safety of drivers. Naturally, it is expected that more knowledge and attitude towards driving laws would result in fewer driving violations. The aim of this research is to investigate both the knowledge and attitude of taxi drivers in the field of traffic rules and regulations in Shiraz city, Fars province, in 2019. Methods. This research is a cross-sectional study, based on which about 1077 taxi drivers were randomly chosen in Shiraz city, Iran. The data collection tool is a demographic information questionnaire and a questionnaire on driving guidance. After collecting these questionnaires, the obtained data were entered into SPSS version 20 and then analyzed by descriptive analyses (mean, standard deviation, and percentage). Afterward, the independent t-test, one-way ANOVA, and Pearson correlation coefficient are implemented and investigated. Results. The mean and standard deviation of knowledge score in drivers were about 26.8 ± 55.2 while the mean and standard deviation of drivers’ attitude were about 98.16 ± 59.3. The results showed that there was a significant relationship between the variables studied (R = −0.07; $P=0.02$ ) and drivers’ attitudes toward driving ( $P=0.01$ ). Conclusion. The results of this research show that the mean scores of knowledge and attitude of taxi drivers in Shiraz city are moderate in terms of driving rules and regulations; moreover, among taxi drivers of increasing age, the average score of knowledge was lower.

Driving Fine and its Relationship with Dangerous Driving Behaviour Among Heavy Vehicle Drivers

Context

There is a significant difference between actual and existing statistics of traffic fines; since some invisible fines and most of the visible traffic violations cannot be recorded by traffic officers. Therefore, dealing with driving fines and road fatalities is considered an important issue in social and public management worldwide.

Aims

Explore the factors associated with unsafe behaviors and getting traffic fines among a sample of Iranian heavy-vehicle professional drivers.

Settings and Design

The present cross-sectional study was conducted in Iran, from February 2019 to September 2020.

Methods and Material

This study used the driver behavior questionnaire (DBQ), demographic and driving characteristics, the number of fines, and structural equation modeling. Also, in this study 320 professional drivers participated.

Statistical Analysis Used

This article used structural equation modeling for Statistical analysis.

Results

The results of structural equation modeling analysis indicated that the data fit well with the theoretical model proposed in this study. The number of fines was directly predicted by both demographic and driving characteristics and risky driving behaviors. A significant relationship was observed between, driving hours, driving experience, and smoking, respectively, with a mistake, slip, and risky violation. There was a negative correlation between education and all four sub-scales of risky driving behaviors.

Conclusions

In order to reduce traffic fines, training courses on increasing attention and precision in drivers' observations and judgments are useful. The courses can decrease traffic violations by trying to change beliefs, attitudes, and social norms. It is therefore helpful to understand the ways to change the drivers' attitudes.

A data-driven Bayesian network for probabilistic crash risk assessment of individual driver with traffic violation and crash records

In recent years, individual drivers' crash risk assessments have received much attention for identifying high-risk drivers. To this end, we propose a probabilistic assessment method of crash risks with a reproducible long-term dataset (i.e., traffic violations, license, and crash records). In developing this method, we used 7.75 million violations and crashes of 5.5 million individual drivers in Seoul, South Korea, from June 2013 to June 2017 (four years). The stochastic process of the Bayesian network (BN), whose structure is optimized by tabu-search, successfully evaluates individual drivers' crash and violation probability. In addition, the cluster analysis classifies drivers into five distinctive groups according to their estimated violation and crash probabilities. As a result, this study found that the estimated average crash rate within a cluster converges with the actual crash rate by the proposed framework without privacy issues. We also confirm that violation records and expected crash probability are strongly correlated, and there is a direct relationship between a driver's previous violations and crash record and the future at-fault crash. The proposed assessment method is valuable in developing proactive driver education programs and safety countermeasures, including adjusting the penalty system and developing user-based insurance by recognizing dangerous drivers and identifying their properties.

Convergent validity of vision based technology (VBT) among professional bus drivers

INTRODUCTION

Due to the relative rarity of crashes, researchers use traffic offenses, police records, public complaints, and In-Vehicle Data Recorder (IVDR) data as proxies for assessing crash risk. In this study, a unique IVDR system, called Vision-Based Technology [(VBT), (Mobileye Inc.)] was used to monitor perilous naturalistic driving events, such as insufficient distance from other vehicles and pedestrian or bicycle rider near-misses. The study aimed to test the convergent validity of VBT as an indicator of crash involvement risk.

METHODS

Data from 61 professional drivers working for a large bus company were analyzed (16 of 77 in the original data cohort were excluded for insufficient VBT data). Data included: recorded VBT data, objective data collected from official records (crash records provided by the bus company, and public complaints of reckless driving), self-report data regarding crash involvement, and police tickets. The correlation between VBT, objective and self-reported data was analyzed. Binary-logistic regression modeling (BLM) was used to calculate the odds ratio (OR) for participants involved in a car crash.

RESULTS

Correlations were found between the total VBT risk score and official crash records, public complaints, and self-reports of crash involvement. The BLM correctly classified 90% of those who were involved in a crash (sensitivity) and 60% of those who were "crash-free" (specificity). The VBT total risk score was the only significant contributing factor to crash risk, and for each point of increase, the odds of being involved in a crash increased by a factor of 1.55.

CONCLUSIONS

It is the first study to provide empirical evidence validating the VBT as an indicator of crash involvement and driver safety among professional bus drivers.

PRACTICAL APPLICATIONS

VBT technology can provide researchers and clinicians a better understanding of bus drivers' risky driving behaviors- a valuable contribution to road safety interventions for this target group.

Analysis of Electric Bicycle Riders' Use of Mobile Phones While Riding on Campus

Based on the theory of rational action (TRA), overconfidence theory (OT), and deterrence theory (DT), this study explores the reasons for mobile phone use by Chinese students riding electronic bicycles (e-bikes) in Fuzhou City. We tested the reliability and validity of an extended TPB, OT and DT questionnaire (with 531 eligible responses) and constructed a structural equation model of mobile phone use behavior while riding e-bikes, based on the improved model. The structural equation model (SEM) is used to evaluate the relationship between the internal factors of mobile phone riding behavior. The results show that the correlation among mobile phone dependence, punishment mechanism, attitude, and controllable operation impacts e-bike riders’ behavior when using mobile phones while riding.

An Analysis of Driving Behavior of Educated Youth in Bangladesh Considering Physiological, Cultural and Socioeconomic Variables

One of the alarming aspects of Bangladesh’s traffic safety is the massive growth in the number of drivers without previous driving instruction or licenses. Proper traffic safety is defined as systems and techniques used to safeguard road users against dying or being severely injured. A driving simulator policy and an environmental model are validated in this research. It aims to create a safe mass transit system with a minimal number of fatalities and injuries. The study focuses on current road and transportation strategies. Educated and internet-using Bangladeshi drivers took part in a questionnaire about their emotional stability on an online platform with more than 100 questions comprising two parts. While one of the part outlines the physiological, cultural, and socioeconomic factors and driver education, in another part, an 18-point Driver’s Behavior Questionnaire was introduced to the responders. About 40% of the surveyed drivers in the poll were inexperienced. However, 49% of people prefer to ride two-wheelers. Moreover, 70% of surveyed drivers hold valid driver’s licenses. At the same time, 35.2% of those were college graduates. Even 34.8% of accidents were caused by excessive speed and non-aggressive driving. In addition, age and degree of education were significant indicators of distracted driving violations. The study’s findings will raise awareness about the country’s undesirable driving patterns, resulting in a safer transit system with fewer accidents and deaths. In addition, the findings may be utilized to improve present road and transit policies and lead to the development of a driving simulator program for Bangladeshis.

Analysis of risky driving behaviors among bus drivers in China: The role of enterprise management, external environment and attitudes towards traffic safety

Several studies have shown that enterprise management (e.g. culture, salary) and external environment (e.g. traffic congestion) predict risky driving behaviors and accident involvement. However, this process has not been systematically investigated in bus drivers. The present study uses structural equation model to assess whether enterprise management and external environment are associated with risky self-reported driving behaviors both directly and indirectly, through the effects of attitudes towards traffic safety in a large sample of bus drivers. Three hundred and thirty-one bus drivers (mean age = 39.5, SD = 5.6 years) completed a structured and anonymous questionnaire measuring enterprise management, external environment, attitudes toward traffic safety, and self-reported risky driving behaviors (i.e., speeding, fatigue driving, running the light) in the last 6 months. Structural equation modeling analysis revealed that enterprise management, and external environment were associated with risky driving behaviors both directly and indirectly. In particular both of them were directly correlated with bus drivers' attitudes toward traffic safety which, in turn, were related to the five types of self-reported risky driving behaviors. The present findings suggest that measures related to the impact factors could be carried out to reduce the probabilities of the risky driving behaviors among bus drivers, such as improving the salary level of bus drivers, setting up bus lanes and priority signals to alleviate road congestion, optimizing shift schedules, implementing effective safety education, etc. These findings can provide the empirical basis for evidence-based road safety interventions in the context of public transport.

The effects of personality and attitude on risky driving behaviour among public van drivers: hierarchical modelling

Background

Traffic injuries have become a significant public health problem in low- and middle-income countries. Several studies have examined the role of personality and attitude toward traffic safety in predicting driving behaviors in diverse types of drivers. Few studies have investigated risky behavior among public passenger van drivers. This study aims to identify the predictors of self-reported risky driving behavior among public van drivers.

Method

A total of 410 public van drivers were interviewed at terminal stations in Bangkok. Hierarchical regression models were applied to determine the effects of demographics, personality traits, and attitude on self-reported risky driving behaviors.

Results

The results indicated that drivers with a high education level, more working days, and high scores for normlessness and anger were more likely to report risky driving behaviors (p < 0.05).

Conclusion

The personality traits and attitude toward speeding account for aberrant self-reported risky driving behavior in passenger van drivers. This could be another empirical basis for evidence-based road safety interventions in the context of public transport.

Analysis of Driver’s Socioeconomic Characteristics Relating to Speeding Behavior and Crash Involvement: A Case Study in Lahore

Speeding is one of the risky behaviors which results in accident involvement causing fatalities and severe injuries. This paper aimed to identify the significant socio-economic characteristics of drivers concerning their speeding behavior and crash involvement. A questionnaire was designed consisting of driver’s demographic features, involvement in an accident, penalty on speed violations, and statements on speeding behavior in terms of exceeding the speed limits by 10 km/h or more on roads with different speed limits of 60, 80, 100, and 120 km/h per standard operating speeds on various road types in Pakistan. This survey was conducted in Lahore city and a total of 551 usable samples were obtained. A latent variable of drivers’ speeding behavior was introduced; factor loadings were estimated, and an observed variable of drivers’ crash experience was defined as the drivers’ crash involvement. Ordered regression analysis using the probit function was conducted on speeding behavior and crash involvement. The ordinal analysis revealed that the drivers’ age, gender, marital status, employment, vehicle engine size, type of vehicle they drive, and driving frequency per day are good predictors of speeding behavior. Similarly, male drivers’ age, vehicle engine size, and type of vehicle they drive were significant predictors of their likelihood to be involved in an accident. The young, single, and male drivers and drivers of cars with an engine capacity above 1.5 L were more likely to speed and be involved in crashes. These findings provide a clear understanding of a specific group of drivers who have a higher probability of speeding and crash involvement. There is a need to focus on specific demographic factors in the formulation of traffic safety policies and managing speedy drivers’ behaviors.

Driving Performance Evaluation of Shuttle Buses: A Case Study of Hong Kong-Zhuhai-Macau Bridge

The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors to risky performance. To achieve this, 1648 records of GPS trajectory data and 8281 records of advance warning message data from Hong Kong–Zhuhai–Macau Bridge shuttle buses were obtained. The temporal and spatial distribution of risky behaviours was analysed. A random parameters negative binomial model was developed to further investigate the relationship between speed-related factors and risky behaviours. The results indicated that the warning of safety distance, lane departure, forward collision, and distraction were more likely to occur on weekdays. The period between 14 and 16 o’clock obtained the highest frequency of safety distance and lane departure warnings. Regarding the model estimation results, indicators reflecting average speed, acceleration, and number of trips per day showed a statistically significant impact on safety distance and lane departure warnings. Also, the acceleration of bus drivers showed a mixed impact on lane departure warnings. Corresponding implications were discussed according to the findings to reduce the frequency of risky behaviours in shuttle bus operations.

Driver behaviour and traffic accident involvement among professional heavy semi-trailer truck drivers in China

The purpose of this study was to develop a driving behavior scale for professional drivers of heavy semi-trailer trucks in China, and study the causes of such driving behavior and its impact on traffic safety operation. Data was processed by IBM SPSS 25. In addition to principal component analysis, Promax rotation, Bartlett's test, Cronbach's alpha, correlation analysis and binary logistic regression were examined. A DBQ with 4 dimensions and 20 items, and a PDBQ with 1 dimension and 6 items were developed for professional drivers of heavy semi-trailer trucks in China. The KMO coefficients of PDBQ and DBQ were 0.822 and 0.852, respectively, and the significant level of Bartlett's popularity test was p < 0.0001. The accident prediction model showed that the variables related to traffic accidents were negligence/lapses and driving time of heavy semi-trailer truck drivers. 1-5 a.m. was found to be the most dangerous period for drivers of medium and heavy semi-trailer trucks, during which accidents were most likely to happen. As negligence/lapses increased by one unit, the probability of traffic accidents increased by 2.293 times.

A Road Safety-Based Selection Methodology for Professional Drivers: Behaviour and Accident Rate Analysis

In this paper, we examine the factors affecting the behaviour of road users and the impact of these factors on professional drivers' reliability and performance. A professional driver is considered as a driver involved in the processes of driving a vehicle as a matter of his/her business or the transportation of passengers or goods by bus or lorry, with higher liability in terms of road safety and requiring a higher degree of maintained attentiveness, constant concentration, and working capacity. This article highlights the process of selecting a professional driver by focusing on the driver's individual and psychophysiological characteristics. An anonymous survey on professional drivers and a statistical analysis of the accidents caused by professional drivers was used to research the impact of fatigue on the behaviour of road users. The conducted statistical analysis demonstrates that the amount of professional driving experience most conducive to driving a vehicle safely was observed at between 29 and 33 years of experience. It was also found that a higher probability of causing an accident after rest days is related to the driver's long period of engagement at work and inadequate rest. This study demonstrates that specific requirements should be applied to the methodologies for selecting professional drivers, the research on the reliability of which aims to develop a concept that enables opting for those drivers able to properly perform hired work, causing minimal losses due to road accidents.

Perfectionism and Eating Behavior in the COVID-19 Pandemic

The novel coronavirus disease 2019 (COVID-19) represents a massive global health crisis leading to different reactions in people. Those reactions may be adaptive or not depending on situational or psychological processes. Disordered eating attitudes and behaviors are likely to be exacerbated by the pandemic through multiple pathways as suggested by Rodgers et al. (2020). Among the psychological variables that may have increased dysfunctional eating attitudes and behaviors as a consequence of the social distancing and isolation, we looked at perfectionism. Perfectionism is a well-recognized risk and maintaining factor of eating-related symptoms and interact with stress increasing the probability of dysfunctional reactions (e.g., Wang and Li, 2017). The present study investigated the relationship between multidimensional perfectionism and eating behaviors by considering the mediating role of psychological distress. Data were collected from two countries (Italy and Spain) by means of an online survey. The samples included 465 (63.4% female) participants from Italy and 352 (68.5% female) from Spain. Participants completed the short form of the Hewitt and Flett Multidimensional Perfectionism Scale (Lombardo et al., 2021) to assess self-oriented, other-oriented and socially prescribed perfectionism, as well as the short form of Three Factors Eating Questionnaire (Karlsson et al., 2000) and the Italian version of Depression Anxiety and Stress Scale-21 (Bottesi et al., 2015), respectively used to assess restrictive, emotional and uncontrolled eating on one hand, and depression, anxiety and stress on the other. Multigroup analysis was performed to test the hypothesized model. Results showed that other-oriented and socially prescribed perfectionism were indirectly related to most of the dysfunctional eating aspects through the mediation of psychological distress, and the pattern obtained was consistent in both countries. These findings evidence that the psychological distress potentially related to the COVID-19 disease mediates the negative impact of interpersonal perfectionism and the tendency to eat in response to negative emotions.

Analysis of safety climate and individual factors affecting bus drivers' crash involvement using a two-level logit model

Although traffic crashes involving buses are less frequent than those involving other vehicle types, the consequences of bus crashes are high due to the potential for multiple injuries and casualties. As driver error is a primary factor affecting bus crashes, driver safety education is one of the main countermeasures used to mitigate crash risk. In China, however, safety education is not as focused as it should be, largely due to the limited research identifying the specific driver behaviors, and potential influences on those behaviors, that are correlated with crashes. The aim of this study is, therefore, to explore the fleet- and driver-level risk factors underlying bus drivers' self-reported crash involvement, including analyzing the effect of psychological distress on the most influential driver-level factors. A survey was conducted of 725 drivers from a large Shanghai bus company, and a random-effects two-level logit model was developed to integrate fleet and individual variables. Results showed that: 1) the fleet-level safety climate explained about 8.5% of the model's variance, indicating it was a valid predictor of self-reported crash involvement; 2) the driver-level factors of drivers' age, seniority, marital status, positive behavior, and driving anger influenced drivers' self-reported crash involvement, but ordinary violations, lapses, aggressive violations, and insomnia were the most influential variables; 3) psychological distress appeared to associate with the high frequency of risky driving behavior and the high severity of driving anger. This study's findings will help bus companies to give more attention to their safety climate and implement more targeted improvements to their driver safety education programs.

Incorporating Personality Traits to Assess the Risk Level of Aberrant Driving Behaviors for Truck Drivers

Economic globalization and the internet economy have resulted in a dramatic increase in freight transportation. Traffic crashes involving trucks usually result in severe losses and casualties. The fatality and injury rates for heavy truck accidents have been 10 times higher than for sedans in Taiwan in recent years. Thus, understanding driving behavior and risk are important for freight carriers. Since personality traits may result in different driving behaviors, the main objective of this study is to apply artificial neural network (ANN) models to predict the frequency of aberrant driving behavior and the risk level of each driver according to drivers’ personality traits. In this case study, relevant information on truck drivers’ personality traits and their tendency to engage in aberrant driving behavior are collected by using respectively a questionnaire and a fleet surveillance system from a truck company. A relative risk level evaluation mechanism is developed considering the frequency and distribution of aberrant driving behavior. The Jenks natural breaks optimization method and the elbow method are adopted to optimally classify 40 truck drivers into 4 aberrant driving behavior levels and 5 driving risk levels. It was found that 5% of drivers were at the highest aberrant driving behavior level, and 7.5% of drivers were at the highest driving risk level. Based on the results, the proposed models show good and stable predictive performance, especially for the class of drivers with excessive rotation speed, hard acceleration, excessive rotation speed, hard deceleration, and driving risk. With the proposed models, the predictive class for aberrant driving behavior and driving risk can be determined by plugging in a driver’s personality traits before or after employment. Based on the prediction results, the manager of a transportation company could plan the training program for each driver to reduce the aberrant driving behavior occurrence.

Driving Behavior That Limits Concentration: A Nationwide Survey in Greece

Human behavior is implicated in most road accidents. The current study examined drivers’ behavior that interferes with decision making and reaction time to an incidence. Adults (≥17 years-old) participated in a questionnaire-based survey for driver’s behavior. Dataset was weighed according to sex, age and education based on the 2011 census. Differences between groups were assessed with Chi-squared tests while logistic regression models were used to identify drivers’ characteristics for specific behaviors. A total 1601 adults participated in the survey—48% males and 52% females. Texting, Global Positioning System (GPS) setting and smoking were observed more by professional drivers and drivers of an urban area, while smoking was also dependent on social class. Drink driving was observed more by males (20% vs. 5% females), while after adjusting for age, the odds of drink driving in males were 5 times higher than females (p < 0.001). A different effect of age depending on the driver’s sex and vice versa was observed regarding phone calls. Drivers’ behavior with distractive potential differed by age, sex, social class and area of residence. Male drivers were more likely to perform drink driving, while professional drivers were more likely to use cell phone for calls and texting, set the GPS and smoke while driving.

Could Road Safety Education (RSE) Help Parents Protect Children? Examining Their Driving Crashes with Children on Board

Recent evidence suggests that driving behavior and traffic safety outcomes of parents may be influenced by the extent to which they receive information and education on road safety, as well as the fact of driving with their children on board, which may increase their risk perception. However, there are no studies specifically addressing the case of crashes suffered while driving with children. Hence, this study aimed to describe the relationship between road safety education-related variables and parents' traffic safety outcomes while driving with children on board. For this cross-sectional study, data was retrieved from a sample composed of 165 Spanish parents-all of them licensed drivers-with a mean age of 45.3 years. Through binary logistic regression (logit) analysis, it was found that factors such as gender, having received road safety education (RSE), and having been sanctioned for the performance of risky driving behavior contribute to modulating the likelihood of suffering crashes while driving with children on board. Gender differences showed a riskier status for male parents. In this study, a set of risk factors explaining the involvement in traffic crashes when driving with children as passengers was identified among parents: gender, traffic sanctions, valuation, and exposure to road safety campaigns. Also, substantial limitations in the self-reported degree of received RSE were found, especially considering that risky driving behavior and traffic crash rates with children on board still have a high prevalence among parents.

The Impact of Two MMPI-2-Based Models of Personality in Predicting Driving Behavior. Can Demographic Variables Be Disregarded?

The driver’s personality is a key human factor for the assessment of the fitness to drive (FTD), affecting driving decisions and behavior, with consequences on driving safety. No previous study has investigated the effectiveness of Minnesota Multiphasic Personality Inventory (MMPI)-2 scales for predicting the FTD. The present study aimed to compare two MMPI-2-based models of normal and pathological personality traits (i.e., Inventory of Driving-related Personality Traits (IVPE)-MMPI vs. Personality Psychopathology Five (PSY-5) scale) in predicting the cognitive FTD. One hundred young and eighty-seven adult active drivers completed the MMPI-2 questionnaire as a measure of personality and a computerized driving task measuring for resilience of attention (Determination Test (DT)), reaction speed (Reaction Test (RS)), motor speed (MS), and perceptual speed (Adaptive Tachistoscopic Traffic Perception Test (ATAVT)). The effects of age, gender, and education were also controlled. Results showed that the models controlled for demographics overperformed those neglecting them for each driving outcome. A negative effect of age was found on each driving task; the effect of gender, favoring males, was found in both the RS and the MS, and the effect of education was found on the DT and the ATAVT. Concerning personality traits, significant effects were found of sensation seeking (IVPE-MMPI) on each outcome; of anxiety (as a measure of emotional instability; IVPE-MMPI) and introversion (PSY-5) on the measures of MS; and of psychopathic deviation (as a measure of self-control; IVPEMMPI) on the DT. The study confirmed the key role of demographic factors in influencing the FTD, further suggesting the usefulness of some MMPI2-based personality scales in the assessment of driving-related personality determinants.

Relationship between using cell phone and the risk of accident with motor vehicles: An analytical cross-sectional study

PURPOSE

Traffic accidents are one of the major health problems in the world, being the first cause of burden of illness and the second leading cause of death in Iran. The Sistan-Baluchestan province is one of the most accidental provinces of Iran with the highest rate of accidents-caused deaths. This study was conducted to determine the risk factors associated with traffic accidents in Zahedan through 2013 to 2016.

METHODS

This analytical cross-sectional study was carried out on 223 drivers from Zahedan who were traumatized by traffic accident and sent to Zahedan hospitals. The data were obtained through interviews taken by the trained interviewers via refereeing to the medical records and collected in the researcher-made checklist. Census was obtained from the study subjects. For data analysis, independent t-test, one-way ANOVA, Chi-square and logistic regression were used with the Stata software version 11.0.

RESULTS

In this study, 223 male subjects with the mean age of (32.54 ± 12.95) years, 39.8% single and 60.2% married, entered for investigation. Most accidents (38.8%) occurred between 12:00 to 17:59. While driving, 47.1% of the study subjects were using cell phones, 89.1% had manual use of mobile phones, 21.9% had a habit of sending short message service (SMS) and 23.4% had sent SMS within 10 min before the accident. The one way analysis of variance showed that the mean age of individuals with marital status, driving experience, education and accident with motorcycle were significantly different (p < 0.05). Also, the multivariate logistic regression test indicated a significant relationship of smoking, ethnicity, insurance and SMS typing while driving with motorcycle accident (p < 0.05).

CONCLUSION

In this study, SMS and smoking while driving had the highest risk among the variables studied in the motorcycle accidents. Therefore, effective education attempting to enhance people's awareness about the consequences of using cell phone and smoking during driving to reduce traffic accidents seems necessary.

Predicting Errors, Violations, and Safety Participation Behavior at Nuclear Power Plants

Commissioning workers at nuclear power plants have long been ignored in previous studies, although their performance is closely related to the overall safety of plants. This study aimed to explain and predict three types of behavior, i.e., errors, violations, and safety participation, of commissioning workers, under the general framework of the theory of planned behavior (TPB) and by considering organization and planning factors. The validity of the model was evaluated with a sample of 167 commissioning workers who completed a self-reported questionnaire. The results showed that perceived behavioral control, along with organization and planning, significantly affected all types of behavior. It was also found that violations and errors were a direct result of attitude. Besides, errors were predicted by subjective norm; unexpectedly, this occurred in a positive way. These findings revealed the underlying mechanisms for the development of errors, violations, and safety participation among commissioning workers and provided practical implications for safety improvement at the commissioning workplace.

Who uses a mobile phone while driving for food delivery? The role of personality, risk perception, and driving self-efficacy

INTRODUCTION

The existing literature on mobile phone use while driving (MPUWD) mainly targets the participants from general population and the young adults, however, few studies pay attention to this form of distracted driving with samples in professional contexts. The present study aims to bridge the gap by identifying the extent of and the motives behind making use of mobile phones while driving for food dispatch among deliveryman.

METHOD

The snowball sampling was used to collect the data (N = 317) through a self-reported questionnaire, including demographics, personality traits, risk perception, driving self-efficacy, and mobile phone use while driving.

RESULTS

Descriptive analysis for the assessed MPUWD behaviors showed that 96.3% (N = 315) of food deliveryman undertook the MPUWD behaviors, though disproportionate distribution among these behaviors existed. Structural equation modeling analysis displayed that psychoticism and driving self-efficacy directly predicted the MPUWD behaviors. The mediating role of driving self-efficacy was verified with the findings that driving self-efficacy completely mediated the relationships that between risk perception and MPUWD behaviors and that between extraversion and MPUWD behaviors, as well as partially mediated the correlation between psychoticism and MPUWD behaviors.

CONCLUSIONS

The present study confirms the prevalence of MPUWD behaviors among food deliveryman. The SEM estimates and bootstrap estimates suggest that personality traits and perceived risk perception per se display limited predicting utility to MPUWD behaviors among food deliveryman, whereas driving self-efficacy and the proposed predictors together well illustrate the assessed MPUWD behaviors among food deliveryman. Practical Applications: These findings imply that developing and implementing intervention efforts in a concerted way would curb these behaviors effectively.

The Drives for Driving Simulation: A Scientometric Analysis and a Selective Review of Reviews on Simulated Driving Research

Driving behaviors and fitness to drive have been assessed over time using different tools: standardized neuropsychological, on-road and driving simulation testing. Nowadays, the great variability of topics related to driving simulation has elicited a high number of reviews. The present work aims to perform a scientometric analysis on driving simulation reviews and to propose a selective review of reviews focusing on relevant aspects related to validity and fidelity. A scientometric analysis of driving simulation reviews published from 1988 to 2019 was conducted. Bibliographic data from 298 reviews were extracted from Scopus and WoS. Performance analysis was conducted to investigate most prolific Countries, Journals, Institutes and Authors. A cluster analysis on authors' keywords was performed to identify relevant associations between different research topics. Based on the reviews extracted from cluster analysis, a selective review of reviews was conducted to answer questions regarding validity, fidelity and critical issues. United States and Germany are the first two Countries for number of driving simulation reviews. United States is the leading Country with 5 Institutes in the top-ten. Top Authors wrote from 3 to 7 reviews each and belong to Institutes located in North America and Europe. Cluster analysis identified three clusters and eight keywords. The selective review of reviews showed a substantial agreement for supporting validity of driving simulation with respect to neuropsychological and on-road testing, while for fidelity with respect to real-world driving experience a blurred representation emerged. The most relevant critical issues were the a) lack of a common set of standards, b) phenomenon of simulation sickness, c) need for psychometric properties, lack of studies investigating d) predictive validity with respect to collision rates and e) ecological validity. Driving simulation represents a cross-cutting topic in scientific literature on driving, and there are several evidences for considering it as a valid alternative to neuropsychological and on-road testing. Further research efforts could be aimed at establishing a consensus statement for protocols assessing fitness to drive, in order to (a) use standardized systems, (b) compare systematically driving simulators with regard to their validity and fidelity, and (c) employ shared criteria for conducting studies in a given sub-topic.

How do fatalistic beliefs affect the attitudes and pedestrian behaviours of road users in different countries? A cross-cultural study

This paper reports on an exploratory investigation of the influence of five different fatalistic belief constructs (divine control, luck, helplessness, internality, and general fatalism) on three classes of self-reported pedestrian behaviours (memory and attention errors, rule violations, and aggressive behaviours) and on respondents' general attitudes to road safety, and how relationships between constructs differ across countries. A survey of over 3400 respondents across Bangladesh, China, Kenya, Thailand, the UK, and Vietnam revealed a similar pattern for most of the relationships assessed, in most countries; those who reported higher fatalistic beliefs or more external attributions of causality also reported performing riskier pedestrian behaviours and holding more dangerous attitudes to road safety. The strengths of relationships between constructs did, however, differ by country, behaviour type, and aspect of fatalism. One particularly notable country difference was that in Bangladesh and, to a lesser extent, in Kenya, a stronger belief in divine influence over one's life was associated with safer attitudes and behaviours, whereas where significant relationships existed in the other countries the opposite was true. In some cases, the effect of fatalistic beliefs on self-reported behaviours was mediated through attitudes, in other cases the effect was direct. Results are discussed in terms of the need to consider the effect of locus of control and attributions of causality on attitudes and behaviours, and the need to understand the differences between countries therein.

Doping Use in High-School Students: Measuring Attitudes, Self-Efficacy, and Moral Disengagement Across Genders and Countries

The main aim of this research was to test the factorial validity and measurement invariance across genders and countries of a set of instruments designed to assess high-school students' attitudes, self-regulatory efficacy, and moral disengagement with regard to doping. A second aim was to examine the criterion and predictive validity of these scales. In total, 402 high-school students from Italy, Romania, and Turkey (40.0, 25.1, and 34.9%, respectively; M age 14.78 years old; SD = 1.04; 52.8% females) completed questionnaires measuring attitudes toward doping, self-regulatory efficacy in refraining from doping, doping-specific moral disengagement, and intention to use doping substances. A confirmatory factor analysis (CFA) supported our expectations with regard to the factor structure of the scales. Multigroup CFAs provided evidence for the full equivalence of the measures across males and females and partial equivalence of the measures across the three countries. The results of the latent mean comparison showed that male students had lower levels of self-regulatory efficacy than females and that Romanian and Turkish students had higher levels of moral disengagement and lower level of self-regulatory efficacy than Italian students. Finally, the results of a structural equation modeling supported the hypothesis that the proposed model predicted students' intentions to use doping, thus generally confirming the criterion and the predictive validity of the measures. These findings suggested the validity of a set of instruments measuring attitudes toward doping, self-regulatory efficacy to refrain from doping, and doping-specific moral disengagement in high-school students from a cross-gender and a cross-cultural perspective and provided meaningful estimates of the differences in the three factors between males and females as well as between Italian, Romanian, and Turkish high-school students.

Multidimensional prediction of work traffic crashes among Spanish professional drivers in cargo and passenger transportation

The aim of this study was to examine the effect of different environmental, mechanical and individual factors associated with fatalities and serious injuries caused by work traffic accidents among cargo and passenger transport drivers (CPTD) in Spain. For this cross-sectional study, national data on work traffic accidents collected in Spain during the last 3 years were analyzed through a regression modeling approach, in order to predict the severity of traffic crashes involving CPTD. Using binary logistic regression analyses, it was found that the type of road and accident, the meteorological, light and vehicle conditions, individual characteristics and risky driving behaviors significantly predict the risk of fatal work traffic accidents and serious injuries. These findings highlight the importance of combining organizational efforts with national road safety policies in order to generate a traffic safety culture among CPTD.

Risk Assessment of Commercial dangerous -goods truck drivers using geo-location data: A case study in China

The primary objective of this study is to understand the relationship between driving risk of commercial dangerous-goods truck (CDT) and exposure factors and find a way to evaluate the risk of specific transportation environment, such as specific transportation route. Due to increasing transportation demand and potential threat to public, commercial dangerous goods transportation (CDGT) has drawn attention from decision makers and researchers within governmental and non-governmental safety organization. However, there are few studies focusing on driving risk assessment of commercial dangerous-goods truck by environmental factors. In this paper we employ survival analysis methods to analyze the impact of risk exposure factors on non-accident mileage of commercial dangerous-good truck and assess risk level of specific driving environment. Using raw location data from six transportation companies in China, we derive a set of 17 risk exposure factors that we use for model parameters estimation. The survival model and hazard model were estimated using the Weibull distribution as the baseline distribution. The results show that four factors - weather, traffic flow, travel time and average velocity have a significant impact on the non-accident mileage of driver in this company, and the assessment results of survival function and hazard function are robust to the different levels of testing data. The employment time has some effect on the results but does not result in a significant difference in most cases, and the task stability has little impact on the results. The findings of this study should be useful for decision makers and transportation companies to better risk assessment of CDT.

Evaluation of penalty and enforcement strategies to combat speeding offences among professional drivers: A Hong Kong stated preference experiment

Speeding has been a great concern around the world due to the occurrence and severity of road crashes. This paper presents an evaluation of the effectiveness of different penalty and camera-based enforcement strategies in curbing speeding offences by professional drivers in Hong Kong. A stated preference survey approach is employed to measure the association between penalty and enforcement strategies and drivers' speed choices. Data suggest that almost all drivers comply with speed limits when they reach a camera housing section of the road. For other road sections, a panel mixed logit model is estimated and applied to understand the effectiveness of penalties and enforcement strategies on driver's speeding behaviors. Driving-offence points (DOPs) are found to be more effective than monetary fines in deterring speeding offences, albeit there is significant heterogeneity in how drivers respond to these strategies. Warning drivers of an upcoming camera-based enforcement section increased speed compliance. Several demographic and employment characteristics, driving history and perception variables also influence drivers' choices of speed compliance. Finally, besides penalty and enforcement strategies, driver education and training programs aimed at addressing aggressiveness/risk-taking traits might help reduce repeated speeding offences among drivers.

Personality traits and risky behavior among motorcyclists: An exploratory study

BACKGROUND

Personality traits have been associated with a series of dysfunctional behaviors, ranging from violence to drug abuse and other risky behaviors. However, few studies have investigated motorcycle riders' personality traits, and no research using the psychobiological model of personality was found. Thus, we investigated the association between temperament and character traits and the occurrence of Motorcycle Accidents (MAs).

METHODS

This cross-sectional study was conducted with a randomly selected of 153 Brazilian motorcycle riders (116 male and 37 female) with a mean age of 31.8randomly selected from the driver's license register, between 2015 and 2018. A sociodemographic questionnaire and the Temperament and Character Inventory (TCI) were used.

RESULTS

Of the 153 participants, 146 (95.4%) reported having been involved in previous accidents, with the main causes as follows: "other drivers' careless behavior" (34.9%); "personal disrespect of traffic rules" (18.5%) and "personal careless behavior" (20.6%). Motorcyclists exhibited higher scores for the temperament factors of novelty seeking and persistence and lower scores for harm avoidance and reward dependence in comparison to the Brazilian population). Considering the reason for motorcycle use, the group of riders that used their motorcycles for work exhibited more temperament factors associated with risk behaviors than those who did not. It was observed that 68.9% of them had low Harm Avoidance (HA) factor scores, whereas 72.1% had high Novelty Seeking (NS) factor scores.

DISCUSSION

The present study highlighted the influences of different personality traits on behaviors, decision-making and risk attitudes that can be potentially harmful to an individual and others. The results provided evidence that a lack of knowledge and experience in riding a motorcycle or any other vehicle, combined with personality traits, contribute to the adoption of risky behaviors that may act as triggers for most causes of Motorcycle Accidents.

Validity and Reliability of the Attitudes toward Traffic Safety Scale in Argentina

The main objective of this research was to investigate the psychometric properties of a Spanish-language version of the Attitudes toward Traffic Safety Scale (ATTS) for the assessment of risky driving attitudes among Spanish-speaking populations. Five hundred and fifty-eight drivers from Argentina participated in the study. Confirmatory factor analysis supported the ATTS three-factor structure: Attitude towards violations and speeding, attitude towards the careless driving of others and attitude towards drinking and driving, χ2(87) = 205.91, p < .001; χ2/df = 2.36; GFI = .94; CFI = .93; TLI = .91; RMSEA = .05; 90% CI [.04, .06]. A model with one higher-order factor (overall attitude toward risky driving) also fits the data. Reliability estimates were acceptable for the total scale (α = .81) and for all subscales (with α values ranging from .74 to .84), and concurrent validity was supported by theoretically expected correlations with self-reported risky driving behavior (r ranging from .27 to .45, ps < .01). Subsequent comparison between zero-order correlation and partial correlation (controlling for Driver Impression Management) between ATTS subscales and self-reported risky driving behavior revealed minor or no effects of social desirability bias. Implications for road safety intervention are discussed.