Risky, aggressive, or emotional driving: addressing the need for consistent communication in research

Problem. Researchers agree that a consistent definition for aggressive driving is lacking. Such definitional ambiguity in the literature impedes the accumulation of accurate and precise information, and prevents researchers from communicating clearly about findings and implications for future research directions. This dramatically slows progress in understanding the causes and maintenance factors of aggressive driving. Summary. This article critiques prevailing definitions of driver aggression and generates a definition that, if used consistently, can improve the utility of future research. Pertinent driving behaviors have been variably labeled in the literature as risky, aggressive, or road rage. The authors suggest that the term “road rage” be eliminated from research because it has been used inconsistently and has little probability of being clarified and applied consistently. Instead, driving behaviors that endanger or have the potential to endanger others should be considered as lying on a behavioral spectrum of dangerous driving. Three dimensions of dangerous driving are delineated: (a) intentional acts of aggression toward others, (b) negative emotions experienced while driving, and (c) risk-taking. Impact on Industry. The adoption of a standardized definition for aggressive driving should spark researchers to use more explicit operational definitions that are consistent with theoretical foundations. The use of consistent and unambiguous operational definitions will increase the precision of measurement in research and enhance authors' ability to communicate clearly about findings and conclusions. As this occurs over time, industry will reap benefits from more carefully conducted research. Such benefits may include the development of more valid and reliable means of selecting safe professional drivers, conducting accurate risk assessments, and creating preventative and remedial dangerous driving safety programs.     

Comparing safety climate factors as predictors of work-related driving behavior

INTRODUCTION: Research suggests safety climate (SC) is a strong predictor of safety-related outcomes in organizations. This study explores the relationship between six SC dimensions and four aspects of work-related driving. METHOD: The SC factors measured were "communication and procedures," "work pressures," "relationships," "safety rules," "driver training," and "management commitment." The aspects of self-reported occupational driving measured were traffic violations, driver error, driving while distracted, and pre-trip vehicle maintenance. RESULTS: Hierarchical regression analyses revealed that the SC factors accounted for significant amounts of variance in all four aspects of work-related driving, over and above the control factors of age, sex, and work-related driving exposure. However, further investigation indicated certain SC factors (particularly safety rules, communication, and management commitment) were more strongly related to specific aspects of work-related driving behavior than others. Together, the SC factors were better able to predict self-reported distraction from the road than the other aspects of driving behavior measured. Implications for occupational safety, particularly for the management of work-related drivers are discussed.     

Prevalence and characteristics of road traffic injuries among young drivers in Oman, 2009–2011

Objectives: Studies from different parts of the world have indicated that the impact of road traffic incidents disproportionally affects young adults. Few known studies have been forthcoming from Arabian Gulf countries. Within Oman, a high proportion of the population is under the age of 20. Coupled with the drastic increase in motorization in recent years, there is a need to understand the state of road safety among young people in Oman. The current research aimed to explore the prevalence and characteristics of road traffic injuries among young drivers aged 17–25 years.

Methods: Crash data from 2009 to 2011 were extracted from the Directorate General of Traffic, Royal Oman Police (ROP) database in Oman. The data were analyzed to explore the impact of road crashes on young people (17–25 years), the characteristics of young driver crashes, and how these differ from older drivers and to identify key predictors of fatalities in young driver crashes.

Results: Overall, young people were overrepresented in injuries and fatalities within the sample time period. Though it is true that many young people in crashes were driving at the time, it was also evident that young people were often victims in a crash caused by someone else. Thus, to reduce the impact of road crashes on young people, there is a need to generally address road safety within Oman. When young drivers were involved in crashes they were predominantly male. The types of crashes these drivers have can be broadly attributed to risk taking and inexperience. Speeding and nighttime driving were the key risk factors for fatalities.

Conclusion: The results highlight the need to address young driver safety in Oman. From these findings, the introduction of a graduated driver licensing system with nighttime driving restrictions could significantly improve young driver safety.     

交通事故致因中的人为因素分析

为改善交通安全状况,减少交通事故,从最主要的因素——人为因素出发,分析其影响。导致事故发生的主要原因是:驾驶员处理交通事件的能力(包括新手、老年、酒精、药物、疲劳、压力等),驾驶员在驾驶时采取冒险行为(包括不正确使用安全带、超速、犯罪、自杀等)。结果表明:新手驾驶、饮酒驾驶、疲劳驾驶、不正确使用安全带驾驶等仍是影响交通安全的主要因素。     

Freight transport and non-driving work duties as predictors of falling asleep at the wheel in urban areas of Crete

BACKGROUND: This study investigated the impact of subjective reports of drowsy driving and non-driving duties on the falling asleep responses and road crash involvement of professional drivers in Crete. An attempt was also made to elucidate other driving parameters, such as freight transportation, which could be potential predictors of risky driving, after controlling for lifestyle patterns. METHOD: A sample of 317 professional drivers was studied through personal interviews. The interview questionnaire included items about sleep and fatigue as contributing factors to falling asleep probability and crash risk. In addition, the drivers reported the type of freight they carried in their last trip, as well as practices such as smoking and alcohol consumption. RESULTS: The first logistic regression analysis showed that the most significant predictors of falling asleep at the wheel were transportation of fruits/vegetables and livestock, non-driving hours of work, insufficient hours of sleep, and smoking. The second logistic regression analysis revealed all the previous items as powerful factors of crash probability, including the transportation of express freight and freezer. IMPACT: The findings of the current study are discussed as they pertain to directions for future studies and for the development of fatigue countermeasures.     

基于加速度干扰和AHP的车辆行驶安全性评价模型

关于行驶中的车辆在交通系统各因素作用下的行驶安全性评价,在现有交通系统四大要素的基础上加入车辆行驶状态,构成"人-车-环境-路-车辆行驶状态"5要素。并对各要素评价指标的选定做了细致的筛选,建立了车辆行驶安全性评价指标体系。其中"人-车-环境-路"因素采用打分的形式确定其参数的分值,并利用层次分析法(AHP)计算各参数权重来构建模型的;"车辆行驶状态"因素则是引入加速度干扰的定义,建立基于道路结构的加速度干扰模型。最后,运用层级分析法建立了总的车辆行驶安全评价模型。     

Parental risk perceptions of childhood pedestrian road safety

Problem: Pedestrian injury is a major hazard to the health of children in most developed countries, including Australia. In a previous study it was found that parental road risk perception is a significant factor associated with their modeling of safe behavior as pedestrians. This study aimed to investigate factors that affect parental road risk perception. Method: This cross-sectional population-based randomized telephone survey aimed to study factors associated with risk perception on pedestrian road safety among parents with young children aged 4–12 years. Results: Five factors were found to be significantly associated with parental risk perception. They included age of child, sex of parent, employment of parent, living environment, and previous injury experience. The results suggested that the age of the child contributed greatest to the variance explained by the regression model. However, other factors remained significant even after adjusting for each other. Discussion: Results were discussed in light of the design and development of childhood pedestrian road safety campaigns. Impact on industry: Parental risk perceptions determine their safe road modeling behavior. In this study, significant factors that affect parental road risk perception have been identified. The information obtained can be used in the design of road safety programs that aim at changing the road risk perception of parents.     

Parent involvement in novice teen driving: rationale, evidence of effects, and potential for enhancing graduated driver licensing effectiveness

Motor-vehicle crash rates are highly elevated immediately after licensure and then decline gradually over a period of years. Young age, risk taking, and inexperience contribute to the problem, but inexperience is particularly important early on. Driving is like other complex, skilled behaviors in which subtle improvements in perception and judgment develop gradually over a period of years. After all, safe driving is more a matter of attention and perception than physical management of the vehicle. Inexperience is particularly linked to driving performance and safety outcomes under certain driving conditions, with driving at night and with teen passengers as the most important cases. Surprisingly, driving outcomes do not appear to be affected by the pre-license training or supervised practice driving. Given the limits of training, safety effects can best be achieved by countermeasures that delay licensure or limit novice teen driving under high risk driving conditions while novices gain experience and develop safety competence. The two complementary approaches of Graduated Driver Licensing policies and parent management have been shown to provide safety effects by limiting the driving conditions of novice teenagers.     

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

Objective: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding.

Methods: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving.

Results: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk.

Conclusions: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.     

Cell phone users, reported crash risk, unsafe driving behaviors and dispositions: a survey of motorists in Maryland

INTRODUCTION: The purpose of this investigation was to identify risky driving behaviors and dispositions that distinguish drivers who use a cell phone while operating a motor vehicle from non-cell phone using drivers. METHOD: Annual telephone surveys were used to identify drivers who reported using a cell phone while driving in the last month (n=1803) and were compared to those who said they did not use cell phones while driving (n=1578). RESULTS: Cell phone using drivers were more likely to report driving while drowsy, going 20 mph over the speed limit, driving aggressively, running a stop sign or red light, and driving after having had several drinks. They were also more likely to have had a prior history of citation and crash involvement than non-cell phone using drivers. Cell phone using drivers also reported they were less careful and more in a hurry when they drive than non-cell phone using drivers. CONCLUSION: Cell phone using drivers report engaging in many behaviors that place them at risk for a traffic crash, independent of the specific driving impairments that cell phone usage may produce. Strategies that combine coordinated and sustained enforcement activities along with widespread public awareness campaigns hold promise as effective countermeasures for these drivers, who resemble aggressive drivers in many respects.     

道路交通环境中驾驶疲劳的生成模型研究

为预防由驾驶疲劳引起的交通事故,有必要研究在道路、交通和环境的综合影响下驾驶疲劳的生成机理。基于生理、心理学中的经典理论,借鉴国内外相关的研究成果,采用理论推理的方法对驾驶疲劳生成过程中驾驶员唤醒水平的变化规律及其影响因素进行分析。在此基础上建立了驾驶疲劳的生成模型,并将模型应用于工程实际。通过驾驶员唤醒水平的变化,指出驾驶疲劳的生成时刻,及其对驾驶时间的规定和道路、景观设计的影响。该模型以唤醒水平为核心,描述驾驶疲劳生成过程中驾驶员唤醒水平的变化规律,强调道路交通环境对驾驶员唤醒水平的影响。     

Commentary: Status of road safety in Asia

Objectives: The objective of this article is to assess the status of road safety in Asia and present accident and injury prevention strategies based on global road safety improvement experiences and discuss the way forward by indicating opportunities and countermeasures that could be implemented to achieve a new level of safety in Asia.

Methods: This study provides a review and analyses of data in the literature, including from the World Health Organization (WHO) and World Bank, and a review of lessons learned from best practices in high-income countries. In addition, an estimation of costs due to road transport injuries in Asia and review of future trends in road transport is provided.

Results: Data on the global and Asian road safety problem and status of prevention strategies in Asia as well as recommendations for future actions are discussed. The total number of deaths due to road accidents in the 24 Asian countries, encompassing 56% of the total world population, is 750,000 per year (statistics 2010). The total number of injuries is more than 50 million, of which 12% are hospital admissions. The loss to the economy in the 24 Asian countries is estimated to around US$800 billion or 3.6% of the gross domestic product (GDP).

Conclusions: This article clearly shows that road safety is causing large problems and high costs in Asia, with an enormous impact on the well-being of people, economy, and productivity. In many Asian low- and middle-income countries, the yearly number of fatalities and injuries is increasing. Vulnerable road users (pedestrians, cyclists, and motorcyclists combined) are particularly at risk. Road safety in Asia should be given rightful attention, including taking powerful, effective actions. This review stresses the need for reliable accident data, because there is considerable underreporting in the official statistics. Reliable accident data are imperative to determine evidence-based intervention strategies and monitor the success of these interventions and analyses. On the other hand, lack of good high-quality accident data should not be an excuse to postpone interventions. There are many opportunities for evidence-based transport safety improvements, including measures concerning the 5 key risk factors: speed, drunk driving, not wearing motorcycle helmets, not wearing seat belts, and not using child restraints in cars, as specified in the Decade of Action for Road Safety 2011–2020. In this commentary, a number of additional measures are proposed that are not covered in the Decade of Action Plan. These new measures include separate roads or lanes for pedestrians and cyclists; helmet wearing for e-bike riders; special attention to elderly persons in public transportation; introduction of emerging collision avoidance technologies, in particular automatic emergency braking (AEB) and alcohol locks; improved truck safety focusing on the other road user (including blind spot detection technology; underride protection at the front, rear, and side; and energy-absorbing fronts); and improvements in motorcycle safety concerning protective clothing, requirements for advanced braking systems, improved visibility of motorcycles by using daytime running lights, and better guardrails.     

Understanding adolescent development: implications for driving safety

PROBLEM: The implementation of Graduated Driver Licensing (GDL) programs has significantly improved the crash and fatality rates of novice teen drivers, but these rates remain unacceptably high. METHOD: A review of adolescent development research was undertaken to identify potential areas of improvement. RESULTS: Research support for GDL was found to be strong, particularly regarding early acquisition of expertise in driving safety (beyond driving skill), and to limitations that reduce opportunities for distraction. GDL regimes are highly variable, and no US jurisdictions have implemented optimal regimes. SUMMARY: Expanding and improving GDL to enhance acquisition of expertise and self-regulation are indicated for implementation and for applied research. Driver training that effectively incorporates safety goals along with driving skill is another target. IMPACT ON INDUSTRY: The insurance industry will benefit from further GDL enhancements. Benefits may accrue to improved driver training, improved simulation devices during training, and automated safety feedback instrumentation.     

A challenge to the assumed generalizability of prediction and countermeasure for risky driving: different factors predict different risky driving behaviors

In road safety, it may be debated whether all risky behaviors are sufficiently similar to be explained by similar factors. The often assumed generalizability of the factors that influence risky driving behaviors has been inadequately tested. Study 1 (N=116) examined the role of demographic, personality and attitudinal factors in the prediction of a range of risky driving behaviors, for young drivers. Results illustrated that different driving behaviors were predicted by different factors (e.g., speeding was predicted by authority--rebellion, while drink driving was predicted by sensation seeking and optimism bias). Study 2 (N=127) examined the generalizability of these results to the general driving population. Study 1 results did not generalize. Predictive factors remained behavior-specific, but different predictor-behavior relationships were observed in the community sample. Overall, results suggest that future research and practice should focus on a multi-factor framework for specific risky driving behaviors, rather than assuming generalizability across behaviors and driving populations.     

Assessing the risk of secondary crashes on highways

IntroductionThe occurrence of “secondary crashes” is one of the critical yet understudied highway safety issues. Induced by the primary crashes, the occurrence of secondary crashes does not only increase traffic delays but also the risk of inducing additional incidents. Many highway agencies are highly interested in the implementation of safety countermeasures to reduce this type of crashes. However, due to the limited understanding of the key contributing factors, they face a great challenge for determining the most appropriate countermeasures.MethodTo bridge this gap, this study makes important contributions to the existing literature of secondary incidents by developing a novel methodology to assess the risk of having secondary crashes on highways. The proposed methodology consists of two major components, namely: (a) accurate identification of secondary crashes and (b) statistically robust assessment of causal effects of contributing factors. The first component is concerned with the development of an improved identification approach for secondary accidents that relies on the rich traffic information obtained from traffic sensors. The second component of the proposed methodology is aimed at understanding the key mechanisms that are hypothesized to cause secondary crashes through the use of a modified logistic regression model that can efficiently deal with relatively rare events such as secondary incidents. The feasibility and improved performance of using the proposed methodology are tested using real-world crash and traffic flow data.ResultsThe risk of inducing secondary crashes after the occurrence of individual primary crashes under different circumstances is studied by employing the estimated regression model. Marginal effect of each factor on the risk of secondary crashes is also quantified and important contributing factors are highlighted and discussed.Practical applicationsMassive sensor data can be used to support the identification of secondary crashes. The occurrence mechanism of these secondary crashes can be investigate by the proposed model. Understanding the mechanism helps deploy appropriate countermeasures to mitigate or prevent the secondary crashes.     

主成分分析法和德尔菲结合法的影响驾驶行为指标构建

为了构建影响驾驶行为的指标,统计了影响驾驶行为的41项因素。针对这些因素,制作了调查问卷,并对各个行业的120名驾驶员发放问卷。对收回的有效问卷结果进行统计,并采用主成分分析法和模糊德尔菲与灰色德尔菲法结合两种方法对问卷结果进行分析。主成分分析与德尔菲结合法都能有效地将驾驶员观点定量化,进而得到对驾驶员行为相对影响较大的指标。比较两种方法的分析结果,运用交叉法得到了19个主要影响驾驶行为的指标。     

Why is the rate of annual road fatalities increasing? A unit record analysis of New Zealand data (2010–2017)

IntroductionRecent increases in road crashes have reversed New Zealand’s formerly declining crash rates to produce annual fatal and serious injury counts that are 49% higher than the lowest rates achieved in 2013. Method: We model twenty-one factors in fatal and serious injury crashes, four years before and after 2013 using logistic regression. Three major factors are significantly different in the period after 2013, when crash rates increased: (1) alcohol as a cause, (2) learner licence holders, and (3) a regional effect for Auckland. Newly defined speed zones are a more common setting for crashes in the period of upturn but there is no coinciding elevated likelihood of ‘speed as a causal factor’. Three factors related to road safety were less common: aged under 25-years old, fatigue, and not wearing a seatbelt. Results: Results are compared to rates of prosecutions for alcohol-related driving offences over this period. It is possible that New Zealand’s successful road safety initiatives of the past have been undermined by reduced levels of enforcement and an unexpected outcome from the graduated driving licence system.     

Inclusion of phone use while driving data in predicting distraction-affected crashes

Introduction: Given the tremendous number of lives lost or injured, distracted driving is an important safety area to study. With the widespread use of cellphones, phone use while driving has become the most common distracted driving behavior. Although researchers have developed safety performance functions (SPFs) for various crash types, SPFs for distraction-affected crashes are rarely studied in the literature. One possible reason is the lack of critical distracted behavior information in the commonly used safety data (i.e., roadway inventory, traffic, and crash counts). Recently, the frequency of phone use while driving (referred to as phone use data) is recorded by mobile application companies and has become available to safety researchers. The primary objective of this study is to examine if phone use data can potentially predict distracted-affected crashes. Method: The authors first integrated phone use data with roadway inventory, traffic, and crash data in Texas. Then, the Random Forest (RF) algorithm was applied to assess the significance of the feature - phone use while driving - for predicting the number of distraction-affected crashes on a road segment. Further, this study developed two SPFs for distraction-affected crashes with and without the phone use data, separately. Both SPFs were assessed in terms of model fitting and prediction performances. Results: RF results rank the frequency of phone use as an important factor contributing to the number of distraction-affected crashes. Performance evaluations indicated that the inclusion of phone use data in the SPFs consistently improved both fitting and prediction abilities to predict distracted-affected crashes. Practical Applications: The phone use data provide new insights into the safety analyses of distraction-affected crashes, which cannot be achieved by only using the conventional roadway inventory and crash data. Therefore, safety researchers and practitioners are encouraged to incorporate the emerging data sources in reducing distraction-affected crashes.     

基于车载机器视觉的汽车安全技术

在描述汽车驾驶操作过程基础上,根据信息获取范围将汽车安全辅助驾驶的机器视觉分为外部信息的机器视觉与内部信息的机器视觉技术,包括视觉增强、视野扩展、道路环境理解、视线跟踪与驾驶疲劳监测;逐个阐述其作用机理,综述其国内外研究现状,并归纳出研究重点;分析了汽车安全辅助驾驶系统中机器视觉技术当前研究不足。笔者认为,低能见度驾驶员视觉增强方法、道路环境理解信息融合以及驾驶疲劳检测等技术需进一步开展研究。     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.