The effect of organizational justice as perceived by occupational drivers on traffic accidents: Mediating effects of job satisfaction

Introduction: Considerable research supports a positive association between the safety climate (which is a direct organizational factor) and safety performance (such as safe driving). However, indirect organizational variables that influence safe driving have gone largely unexplored. This study contributes to safety research by examining the relationship between organizational justice, which is a distal organizational factor, and traffic accidents and the mediating role of job satisfaction. Method: 233 occupational drivers employed by taxi and bus companies in South Korea participated in the study. Regression analysis was conducted using police records on participants' on-the-job traffic accidents. Results: The analysis shows that the mediation model is statistically significant. That is, drivers with a lower level of perceived organizational justice showed a higher frequency of traffic accidents, and the mediating effect of job satisfaction was also significant. Based on the results, implications and limitations are discussed. Practical applications: The findings demonstrate that in order to decrease traffic accidents, transportation companies would benefit by examining distal factors such as organizational justice. This approach suggests that the conventional framework for safety management should be broadened to include aspects of the entire organization.     

Traffic climate and driver behaviors: The moderating role of driving skills in Turkey and China

Introduction: While road traffic accidents and fatalities are a worldwide problem, the rates of road traffic accidents and fatalities show differences among countries. Similarly, driver behaviors, traffic climate, and their relationships also show differences among countries. The aim of the current study is to investigate the moderating effect of driving skills on the relationship between traffic climate and driver behaviors by country. (Turkey and China). Method: There were 294 Turkish drivers and 292 Chinese drivers, and they completed the Traffic Climate Scale, the Driving Skills Inventory, and the Driver Behavior Questionnaire. The moderated moderation analyses were conducted with Hayes PROCESS tool on SPSS. Results: The results showed that safety skills moderated the relationship between internal requirements and violations both in Turkey and China. Safety skills also moderated the relationship between internal requirements and errors only in China and the relationship between functionality and violations in Turkey. Perceptual-motor skills moderated the relationships between external affective demands and errors, and also the relationship between internal requirements and positive driver behaviors in Turkey. It can be inferred that driving skills has different influences on traffic climate-driver behaviors relationship in different cultures and there might be cultural differences in the evaluation of drivers’ own driving skills. Practical Applications: Among driving skills, safety skills have a more critical role to increase road safety by decreasing number of violations. Interventions to increase safety skills of drivers might be promising for road safety.     

Individual,business-related,and work environment factors associated with driving tired among taxi drivers in two metropolitan U.S. cities

Introduction: Violence-related events and roadway incidents are the leading causes of injury among taxi drivers. Fatigue is under-recognized and prevalent in this workforce and is associated with both injury outcomes. We describe the association of individual, business-related, and work environment factors with driving tired among taxi drivers in two very different cities. Method: We developed a comprehensive survey for licensed taxi drivers. We trained surveyors to administer the 30-min survey using systematic sampling among taxi drivers waiting for fares in two large U.S. cities: the Southwest (City 1) and the West (City 2). A driving tired scale of the Occupational Driver Behavior Questionnaire was the outcome. Multivariate logistic models described driving tired behavior in city-specific models using adjusted Odds Ratios (ORadj). Results: City 1 and City 2 had 496 and 500 participants, respectively. Each driving tired behavior was significantly more prevalent in City 2 than City 1 (p < .05). There were more variables and a greater diversity of variables in the models describing drowsy driving in City 1 than City 2. In City 1, variables describing negative safety climate (ORadj = 1.15), socio-demographic groups (identifying as Asian, educational attainment), passenger-related violence (ORadj = 1.79), and company tenure (ORadj = 1.15) were associated with driving tired. In City 2, high perceived safety training usefulness (ORadj = 0.48) was associated with driving tired. A risk factor for driving tired that was common to both cities was job demands (ORadj = 1.21 in City 1; 1.43 in City 2). Conclusions: These findings represent two diverse taxi populations driving in two geographically distinct regions that differ in safety regulation. It is important that safety measures that include fatigue awareness training are reaching all drivers. Fatigue management training should be integrated into driver safety programs regardless of location. Practical applications: Fatigue management strategies that recognize individual factors, business-related characteristics, and work environment are an important component of road safety and are particularly relevant for occupational drivers.     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

女性驾驶人特性与行为机制研究现状及展望

为系统地认识女性驾驶人的驾驶特性,分析其驾驶行为,从女性驾驶人交通事故数据统计、致因和心理、生理、“药驾”等因素,梳理国内外女性驾驶人驾驶特性及行为机制的研究成果,总结主流研究角度、方法和内容,并展望其未来研究趋势。对文献的梳理和分析表明:导致女性驾驶人交通事故的因素主要包括人格、认知等心理特征和视觉能力、应激反应等生理特征,同时“药驾”也影响着驾驶特性与行为。剖析了女性驾驶人特性及行为机制研究目前存在的不足之处,对未来的研究提出了建议。并针对女性驾驶人群体在各种道路交通环境中开展有效的模拟驾驶培训和教育,进而全面提升中国女性驾驶人的交通安全水平。     

Modelling the relationship of driver license and offense history with fatal and serious injury (FSI) crash involvement

Introduction: Previous research has indicated that increases in traffic offenses are linked to increased crash involvement rates, making reductions in offending an appropriate measure for evaluating road safety interventions in the short-term. However, the extent to which traffic offending predicts fatal and serious injury (FSI) crash involvement risk is not well established, prompting this new Victorian (Australia) study. Method: A preliminary cluster analysis was performed to describe the offense data and assess FSI crash involvement risk for each cluster. While controlling demographic and licensing variables, the key traffic offenses that predict future FSI crash involvement were then identified. The large sample size allowed the use of machine learning methods such as random forests, gradient boosting, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. This was done for the ‘all driver’ sample and five sometimes overlapping groups of drivers; the young, the elderly, and those with a motorcycle license, a heavy vehicle license endorsement and/or a history of license bans. Results: With the exception of the group of drivers who had a history of bans, offense history significantly improved the accuracy of models predicting future FSI crash involvement using demographic and licensing data, suggesting that traffic offenses may be an important factor to consider when analyzing FSI crash involvement risk and the effects of road safety countermeasures. Conclusions: The results are helpful for identifying driver groups to target with further road safety countermeasures, and for showing that machine learning methods have an important role to play in research of this nature. Practical Application: This research indicates with whom road safety interventions should particularly be applied. Changes to driver demerit policies to better target offenses related to FSI crash involvement and repeat traffic offenders, who are at greater risk of FSI crash involvement, are recommended.     

Behavior and lifestyle characteristics of male Kuwaiti drivers

Introduction: The high traffic accident risk among young drivers is a well-known and well-documented fact in most countries. Lifestyle has proven to affect driving behavior as well as accident risk. This study covers the lifestyle component of the problems related to young male Kuwaiti drivers’ accident risk. Methods: The purpose of the study is to measure the relationship between lifestyle and accident risk. Lifestyle is measured through a questionnaire, where 302 male Kuwaiti drivers (mean age = 28 years; range 25-35 years) answer 39 questions related to behavioral and social factors, road conditions, police enforcement, and life satisfaction. They also report their involvement in accidents and traffic violations. Results: The questionnaire's validity and reliability (Cronbach's alpha = 0.7) were achieved. Principal component analysis reduced the 39 items on the questionnaire to 5 factors. Inadequate police enforcement is strongly correlated (r = 0.862) to accident risk and traffic violations and is thus considered the best predictor of traffic accidents in Kuwait. Impact on Industry: As driving-related incidents (on-the-job and off-the-job) are a significant source of fatalities and lost-work-days, the study points to the importance of considering cultural factors in the design of comprehensive safety programs for industry.     

Motorcycle safety among motorcycle taxi drivers and nonoccupational motorcyclists in developing countries: A case study of Maoming,South China

Objective: An increasing number of motorcycle taxis have been involved in traffic crashes in many developing countries. This study examines the characteristics of both motorcycle taxi drivers and nonoccupational motorcyclists, investigates the risks they pose to road safety, and provides recommendations to minimize their risks.

Methods: Based on the data collected from a questionnaire survey of 867 motorcycle taxi drivers and 2,029 nonoccupational motorcyclists in Maoming, South China, comparisons were made to analyze differences of personal attributes, attitudes toward road safety, and self-reported behavior of the 2 groups.

Results: Results of the chi-square tests show that not only motorcycle taxi drivers but also nonoccupational motorcyclists in Maoming held poor attitudes toward road safety and both groups reported unsafe driving behavior. There is much room for improving local road safety education among all motorcyclists in Maoming. Yet, motorcycle taxi drivers were more likely to pose road safety risks than nonoccupational motorcyclists under some circumstances, such as speeding late at night or early in the morning, not requiring passengers to wear helmets, and running a red light. The results of the binary logistic regression model show that possessing a vehicle license for a motorcycle or not was the common significant predictor for unsafe driving behavior of motorcycle taxi drivers and nonoccupational motorcyclists. Therefore, enforcement against all motorcyclists not showing vehicle licenses for their motorcycles should be stepped up.

Conclusion: Motorcycle safety is largely poor in Maoming. Therefore, efforts to improve motorcycle safety should be strengthened by targeting not only motorcycle taxi drivers but also nonoccupational motorcyclists.     

Brazilian adaptation of the driving anger expression inventory: testing its psychometrics properties and links between anger behavior,risky behavior,sensation seeking,and hostility in a sample of Brazilian undergraduate students

Introduction: In Brazil, driver aggressiveness in road traffic is a critical issue and could be an important contributing factor to the high number of traffic accidents. Because no instruments are available in Portuguese to register driving aggressiveness or driving anger in Brazil, we adapted English instruments into the Brazilian context. The aims of this study were to provide a Brazilian adaptation of the Driving Anger Expression Inventory (DAX) and to try to validate it by testing its psychometric properties and investigating its relationships with risky driving behaviors (DBQ), road accidents, driving sensation seeking, and hostility. Method: The Brazilian adaptations of the DAX, DBQ, the Driving Sensation Seeking Scale (DSSS) and the hostility Scale were administered to a sample of 512 undergraduate students (with a mean age of 23.7 years, 52.1% men). Results: Confirmatory factor analysis of the Brazilian DAX (DAX-BR) items yielded a four-factor solution with 43 items, which obtained the best goodness-of-fit to the data. Cronbach’s alpha for the DAX-BR factors ranged from 0.69 to 0.88. Other results on validity were a positive correlation (range 0.39–0.59) between the factors of the DAX-BR, DSSS, and DBQ. Conclusion: DAX-BR as the same structure as the original and is a reliable instrument for use with young drivers. Other studies should be conducted to further validate the DAX-BR in different types of populations such as older and more experienced drivers, professional drivers, and traffic regulation offenders whose driver's license has been taken away. Practical applications: This Brazilian version can be recommended for the assessment of driving anger expression in Brazil among young drivers in view of helping them driver more safely, and in particular to reduce traffic violations.     

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers

Introduction: This article analyzes the effect of driver’s age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector. Method: We investigate differences in the severity of traffic crashes among two subgroups of older drivers –young-older (65–75) and old-older (75+), and findings are compared with the age interval of drivers under 65. Here, we draw on data for 2016 provided by Spanish Traffic Authority. Parametric and semi-parametric regression models are applied. Results: We identified the factors related to the crash, vehicle, and driver that have a significant impact on the probability of the crash being slight, serious, or fatal for the different age groups. Conclusions: We found that crash severity and the expected costs of crashes significantly increase when the driver is over the age of 75. Practical Applications: Our results have obvious implications for regulators responsible for road safety policies – most specifically as they consider there should be specific driver licensing requirements and driving training for elderly – and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets.     

Investigation of accidents involving powered two wheelers and bicycles – A European in-depth study

Introduction: The number of road fatalities have been falling throughout the European Union (EU) over the past 20 years and most Member States have achieved an overall reduction. Research has mainly focused on protecting car occupants, with car occupant fatalities reducing significantly. However, recently there has been a plateauing in fatalities amongst ‘Vulnerable Road Users’ (VRUs), and in 2016 accidents involving VRUs accounted for nearly half of all EU road deaths. Method: The SaferWheels study collected in-depth data on 500 accidents involving Powered Two-Wheelers (PTWs) and bicycles across six European countries. A standard in-depth accident investigation methodology was used by each team. The Driver Reliability and Error Analysis Method (DREAM) was used to systematically classify accident causation factors. Results: The most common causal factors related to errors in observation by the PTW/bicycle rider or the driver of the other vehicle, typically called ‘looked but failed to see’ accidents. Common scenarios involved the other vehicle turning or crossing in front of the PTW/bicycle. A quarter of serious or fatal injuries to PTW riders occurred in accidents where the rider lost control with no other vehicle involvement. Conclusions: Highly detailed data have been collected for 500 accidents involving PTWs or bicycles in the EU. These data can be further analyzed by researchers on a case-study basis to gain detailed insights on such accidents. Preliminary analysis suggests that ‘looked but failed to see’ remains a common cause, and in many cases the actions of the other vehicle were the critical factor, though PTW rider speed or inexperience played a role in some cases. Practical Applications: The collected data can be analyzed to better understand the characteristics and causes of accidents involving PTWs and bicycles in the EU. The results can be used to develop policies aimed at reducing road deaths and injuries to VRUs.     

Taxi driver speeding: Who,when, where and how? A comparative study between Shanghai and New York City

Objective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?)

Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.

Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.

Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.     

Analysis of effects of driver’s evasive action time on rear-end collision risk using a driving simulator

Introduction: Driver’s evasive action is closely associated with collision risk in a critical traffic event. To quantify collision risk, surrogate safety measures (SSMs) have been estimated using vehicle trajectories. However, vehicle trajectories cannot clearly capture presence and time of driver’s evasive action. Thus, this study determines the driver’s evasive action based on his/her use of accelerator and brake pedals, and analyzes the effects of the driver’s evasive action time (i.e., duration of evasive action) on rear-end collision risk. Method: Fifty drivers’ car-following behavior on a freeway was observed using a driving simulator. An SSM called “Deceleration Rate to Avoid Crash (DRAC)” and the evasive action time were determined for each driver using the data from the driving simulator. Each driver tested two traffic scenarios – Cars and Trucks scenarios where conflicting vehicles were cars and trucks, respectively. The factors related to DRAC were identified and their effects on DRAC were analyzed using the Generalized Linear Models and random effects models. Results: DRAC decreased with the evasive action time and DRAC was closely related to drivers’ gender and driving experience at the road sections where evasive action to avoid collision was required. DRAC was also significantly different between Cars and Trucks scenarios. The effect of the evasive action time on DRAC varied among different drivers, particularly in the Trucks scenario. Conclusions: Longer evasive action time can significantly reduce crash risk. Driver characteristics are more closely related to effective evasive action in complex driving conditions. Practical Applications: Based on the findings of this study, driver warning information can be developed to alert drivers to take specific evasive action that reduces collision risk in a critical traffic event. The information is likely to reduce the variability of the driver’s evasive action and the speed variations among different drivers.     

营运驾驶员驾驶事故影响因素仿真研究

解决营运驾驶员驾驶事故频发的不安全行为问题,基于复杂适应系统（CAS）理论和多主体建模与仿真（ABMS）方法,构建营运驾驶员驾驶事故模型。通过调节车辆状况、管理者管理监督水平、营运驾驶员情绪状态、安全教育水平、驾驶经验和环境综合条件等因素,运用NetLogo仿真平台分析安全管理水平、营运驾驶员安全责任意识、心理负荷水平对驾驶事故的影响。研究表明:营运驾驶员驾驶事故的发生系统是一种典型的CAS,营运驾驶员驾驶事故是三大主体属性和行为环境交互的结果,且交互作用程度不同。因此,运输企业要考虑多种因素,采取相应的措施来降低营运驾驶员驾驶事故的发生。     

Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions,road characteristics and accident types

IntroductionFreeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the “link role” of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident. Method: A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established. Results: The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions.     

Knowledge,attitudes and practices of occupational risks in Colombian taxi drivers

Objective. The objective of this study was to learn about the health and safety strategies in a sample of taxi drivers in Bucaramanga, Colombia. Methods. A cross-sectional study was conducted among 138 taxi drivers. A survey was used to identify the socio-demographic and working characteristics, knowledge, attitudes and practices according to their occupational risk. Results. Eighty-five percent of the workers labored 9–15?h/day. Of those who suffered accidents, 27% were not affiliated to an occupational risk administrator (p = 0.028). Of the workers who had a work-related accident, 58% considered that the use of a cell phone while driving would not always reduce their attention, 50% always used their seat belt and 7% took active breaks and wore their seat belt (p = 0.01). Conclusions. Within this group of taxi drivers, having or believing to possess knowledge regarding an occupational risk did not ensure that they had a safe attitude or safe working practices.     

Why are powered two wheeler riders still fatally injured in road junction crashes? – A causation analysis

Introduction: Powered Two Wheeler (PTW) crashes continue to be a road safety concern with a plateauing of the number of associated fatalities. Method: Forty one UK fatal or serious injury crashes involving a PTW and another vehicle at a junction were examined. Crash causation was analysed using the Driver Reliability and Error Analysis Method (DREAMv3.2). Crashes were split into two groups: Group A, where the other vehicle was travelling in the opposite direction to the PTW and commenced a right turn across the PTW’s path; and Group B where the other vehicle turned right out of a side road (or entrance) across the PTW’s path. Results: Overall, the factor that led directly to the crash (phenotype) was most commonly ‘too high speed’ or ‘too late action’ for the motorcyclist and ‘too early action’ for the other driver. Missed or late observations were contributory factors for both PTW riders and other vehicle drivers. Some differences between groups were observed with the PTW riders in Group B more likely to have ‘insufficient skills’ and the other vehicle drivers in Group A more likely to have ‘attention allocation’ as a causation factor. For both groups the crashes occurred because the other vehicle failed to give way to the PTW with causation chains that suggest ‘looked but failed to see’ is still an issue in this type of crash. The excessive speed of the PTW contributed to some crashes. Conclusions: This analysis suggests that drivers failing to give way to PTW riders at junctions is still a problem. This may relate to the ‘looked but did not see’ phenomenon. Causation differences were observed between the examined groups. Practical considerations: The DREAM methodology is an effective tool in analysing crash data from police collision investigation reports. Different countermeasures may be necessary to prevent different types of junction crashes.     

Studying freeway merging conflicts using virtual reality technology

Introduction: This research aims to investigate the perceptions and reactions of drivers regarding freeway merging situation, utilizing a new approach with the basis of a multilevel simulation platform which incorporates virtual reality (VR) technology. Methods: A VR driving environment integrated with traffic micro-simulation was developed to evaluate driving behaviors and the impact of merging decisions in terms of traffic conflicts. The driving experiments were conducted under a variety of circumstances, including varying traffic flows and the presence of ramp metering. The Surrogate Safety Assessment Model (SSAM) was utilized to extract the number of conflicts from the micro-simulation results. Results: The final results indicated that the probability of conflict has a positive correlation with traffic flow, while conflict frequency at freeway merges is affected by the presence of ramp metering due to its potentiality to enhance driver decisions and reduce the drivers’ pressure when they make maneuvers. Practical Applications: The findings reveal that the proposed VR simulation platform is a useful tool to improve the safety of freeway merging. It has the potential to enhance driver skills and can also be used in the study of human–machine interaction.     

Risk factors associated with truck-involved fatal crash severity: Analyzing their impact for different groups of truck drivers

Introduction: Fatal crashes that include at least one fatality of an occupant within 30 days of the crash cause large numbers of injured persons and property losses, especially when a truck is involved. Method: To better understand the underlying effects of truck-driver-related characteristics in fatal crashes, a five-year (from 2012 to 2016) dataset from the Fatality Analysis Reporting System (FARS) was used for analysis. Based on demographic attributes, driving violation behavior, crash histories, and conviction records of truck drivers, a latent class clustering analysis was applied to classify truck drivers into three groups, namely, ‘‘middle-aged and elderly drivers with low risk of driving violations and high historical crash records,” ‘‘drivers with high risk of driving violations and high historical crash records,” and ‘‘middle-aged drivers with no driving violations and conviction records.” Next, equivalent fatalities were used to scale fatal crash severities into three levels. Subsequently, a partial proportional odds (PPO) model for each driver group was developed to identify the risk factors associated with the crash severity. Results' Conclusions: The model estimation results showed that the risk factors, as well as their impacts on different driver groups, were different. Adverse weather conditions, rural areas, curved alignments, tractor-trailer units, heavier weights and various collision manners were significantly associated with the crash severities in all driver groups, whereas driving violation behaviors such as driving under the influence of alcohol or drugs, fatigue, or carelessness were significantly associated with the high-risk group only, and fewer risk factors and minor marginal effects were identified for the low-risk groups. Practical Applications: Corresponding countermeasures for specific truck driver groups are proposed. And drivers with high risk of driving violations and high historical crash records should be more concerned.     

Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran

Introduction: Digital billboards (DBs) are a competing factor for attracting drivers’ attention; evidence shows that DBs may cause crashes and vehicle conflicts because they catch drivers’ attention. Because of the complexity of a system that includes road conditions, driver features, and environmental factors, it is simply not possible to identify relationships between these factors. Thus, the present study was conducted to provide a well-organized procedure to analyze the effects of DBs on drivers’ behavior and measure factors responsible for drivers’ distraction in Babol, Iran, as a case study. Method: Corresponding data were collected through a Naturalistic Driving Study (NDS) of 78 participants when facing DBs (1,326 samples). These data were analyzed by applying structural equation modeling (SEM) to concurrently recognize relationships between endogenous and exogenous variables. Human, environmental, and road factors were determined as exogenous latent variables in a model to evaluate their influences on drivers’ distraction as an endogenous variable. Results: The results showed that road, environmental, and human factors reciprocally interact with drivers’ distraction, although the estimated coefficient of human factors was more of a factor than that of the other groups. Furthermore, younger drivers, beginner drivers, and male drivers (as human factors); night and unclear weather like a rainy day (as environmental factors); and installing DBs at complicated traffic positions like near-intersections (as road factors) were determined to be the main factors that increase the possibility of drivers’ distraction. Finally, model assessment was suggested using the goodness-of-fit indices.