Classification of errors contributing to rail incidents and accidents: A comparison of two human error identification techniques

Identifying the errors that frequently result in the occurrence of rail incidents and accidents can lead to the development of appropriate prevention and/or mitigation strategies. Nineteen rail safety investigation reports were reviewed and two error identification tools, the Human factors analysis and classification system (HFACS) and the Technique for the retrospective and predictive analysis of cognitive errors (TRACEr-rail version), used as the means of identifying and classifying train driver errors associated with rail accidents/incidents in Australia. We aimed to identify the similarities and differences between the techniques in their capacity to identify and classify errors and also to determine how consistently the tools are applied. The HFACS analysis indicated that slips of attention (i.e. ‘skilled based errors’) were the most common ‘unsafe acts’ committed by drivers. The TRACEr-rail analysis indicated that most ‘train driving errors’ were ‘violations’ while most ‘train stopping errors’ were ‘errors of perception’. Both tools identified the underlying factors with the largest impact on driver error to be decreased alertness and incorrect driver expectations/assumptions about upcoming information. Overall, both tools proved useful in categorising driver errors from existing investigation reports, however, each tool appeared to neglect some important and different factors associated with error occurrence. Both tools were found to possess only moderate inter-rater reliability. It is thus recommended that the tools be modified, or a new tool be developed, for complete and consistent error classification.     

Occupational Cognitive Failure and Its Relationship With Unsafe Behaviors and Accidents

Objectives. The aim of this study was to assess the relationship between occupational cognitive failures (OCFs) and unsafe behaviors, accidents and driving offences among municipal bus drivers in Tehran, Iran. Methods. Systematic random sampling was used to select 190 drivers from 3 transport and traffic Tehran districts. Data were collected with the occupational cognitive failure questionnaire (OCFQ), the driver behavior questionnaire and a data collection form. Results. The mean (SD) numbers of driving-related offences and road traffic accidents were 1.5 (2.6) and 0.37 (1.0), respectively. The mean (SD) numbers of deliberate driving violations, unintended violations, driving slips and mistakes were 6.97 (5.5), 1.61 (1.5), 13.6 (9.0) and 4.53 (3.28), respectively. The mean (SD) number of the OCFs was 28.9 (20.5). A significant correlation was found between occupational cognitive error and unsafe driving behavior subscales. The stepwise logistic regression results showed that, while controlling the effects of confounding factors, the OCF predicts 6%, 9%, 15% and 9% of deliberate violations, unintended violations, driving slips and driving mistakes, respectively. Conclusion. The results of this study show that the score of the OCFQ is a predictor of unsafe driving behaviors and its subscales.     

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.     

Examining the relationship between driver distraction and driving errors: A discussion of theory, studies and methods

Over the past two decades the concept of driver distraction has been the focus of intense research attention. One aspect of distraction for which there has been limited systematic research, however, is its role in driver error causation. This article presents a review of the distraction literature with a view to elucidating what is currently known about the types of driving errors that distraction contributes to and the mechanisms by which distraction induces these errors. The review revealed a number of fundamental gaps in our knowledge, including the number and nature of errors made by drivers when distracted; the mechanisms by which distraction causes errors; whether and how distraction disrupts drivers’ ability to recover from errors; and how system-wide factors moderate the relationship between distraction and error. In closing, we attempt to identify the most appropriate theoretical and methodological approach to drive the integrated study of distraction and error forward. We conclude that it is only through the adoption of a systems approach that integrated countermeasures can be proposed and implemented to mitigate driver errors caused by distraction.     

Higher cue utilization in driving supports improved driving performance and more effective visual search behaviors

IntroductionOnce qualified, drivers rarely receive objective feedback concerning their performance. This is especially the case in the context of cognitive skills such as situation assessment. The aim of this study was to test the construct validity of an online assessment of motor-vehicle driver cue utilization that forms the foundation for situation assessment. Method: Seventy-one undergraduate Psychology students with broadly comparable driving experience completed a motor-vehicle driving version of EXPERTise 2.0, an online tool that enables inferences concerning the utilization of cues based on responses to task-related stimuli. They also completed a simulated driving task while fitted with an eye tracking device, during which a range of hazards were presented with participants’ responses recorded. Results: The results indicated that higher cue utilization was associated with fewer driving errors and collisions, fewer visual fixations, and fewer saccades in comparison to participants with lower cue utilization. Conclusion: The results provide support for the construct validity of EXPERTise 2.0 as an effective measure of cue utilization in the context of driving.Practical applicationsProviding comparative feedback to drivers concerning their development of situation assessment skills may provide opportunities for further training and development, thereby reducing the likelihood of motor-vehicle accidents.     

Impact of impulsiveness, venturesomeness, and empathy on driving by older adults

PROBLEM: Although personality characteristics such as impulsiveness have been linked to the driving safety and driving habits of young and middle-aged adults, little research has focused on the role of personality in older driver behavior. METHOD: Using the IVE questionnaire in an exploratory study, three personality dimensions (impulsiveness, venturesomeness, and empathy) were measured in 305 older drivers (ages 57-87 years old). In addition, the Driving Habits Questionnaire was used to estimate driving exposure, and the Driver Behavior Questionnaire (DBQ) was used to estimate driving errors and violations. State-recorded crash data were made available by the state public safety agency. RESULTS: Subjects who reported four or more driving errors had higher impulsivity and empathy scores and lower venturesomeness scores. Subjects reporting driving violations were more likely to have high impulsivity scores. Driving six or more places per week was associated with lower levels of impulsivity. IMPACT: These results suggest that a comprehensive understanding of driving problems among older adults should also include a consideration of personality dimensions. In doing so, the challenges faced in the interpretation of self-report instruments on driving behaviors must be acknowledged, with a move in research toward greater reliance on more objective measures of driving behavior when assessing the impact of personality variables.     

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.     

Predictability of clinical assessments for driving performance

PROBLEM: As the number of older drivers grows, it is increasingly important to accurately identify at-risk drivers. This study tested clinical assessments predictive of real-time driving performance. METHOD: Selected assessment tools considered important in the identification of at-risk older drivers represented the domains of vision, cognition, motor performance, and driving knowledge. Participants were administered the battery of assessments followed by an on-road test. A univariate analysis was conducted to identify significant factors (<.05) to be included in a multivariate regression model. RESULTS: Assessments identified as independently associated with driving performance in the regression model included: FACTTM Contrast sensitivity slide-B, Rapid Pace Walk, UFOV rating, and MMSE total score. DISCUSSION: The domains of vision, cognitive, and motor performance were represented in the predictive model. SUMMARY: Due to the dynamic nature of the driving task, it is not likely that a single assessment tool will identify at risk drivers. IMPACT ON INDUSTRY: By standardizing the selection of clinical assessments used in driving evaluations, practitioners should be able to provide services more efficiently, more objectively, and more accurately to identify at-risk drivers.     

Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems

Recent research indicates that driver error contributes to up to 75% of all roadway crashes. Despite this, only relatively little is currently known about the types of errors that drivers make and of the causal factors that contribute to these errors being made. This article presents an overview of the literature on human error in road transport. In particular, the work of three pioneers of human error research, Norman, Reason and Rasmussen, is scrutinised. An overview of the research on driver error follows, to consider the different types of errors that drivers make. It was found that all but one of these does not use a human error taxonomy. A generic driver error taxonomy is therefore proposed based upon the dominant psychological mechanisms thought to be involved. These mechanisms are: perception, attention, situation assessment, planning, and intention, memory and recall, and action execution. In addition, a taxonomy of road transport error causing factors, derived from the review of the driver error literature, is also presented. In conclusion to this article, a range of potential technological solutions that could be used to either prevent, or mitigate, the consequences of the driver errors identified are specified.     

Assessment of older drivers: relationships among on-road errors, medical conditions and test outcome

PROBLEM: It is essential that driver licensing authorities have a valid and reliable system for evaluating older drivers' continuing competency; road tests are usually required as part of such a system. This study sought to find information about the nature of driving errors made during license review tests, and about relationships between error type and test outcome for older drivers. METHOD: Data from licensing authority files from 533 road tests during a 12-month period were analyzed; medical and other referral information was included. Average driver age was 76 years. Performance scores were generated for intersection negotiation, lane changing, low speed manoeuvres, positioning and speed control, safety margin, and car control. RESULTS: Logistic regression analysis showed that test outcome was well predicted by a subset of driving performance scores; adding driver age to the model explained very little variance. Age alone was strongly associated with outcome. Relationships between referral information and test outcome are also reported. IMPACT: Results highlight several factors relevant to the development of more valid and reliable road tests for older 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.     

Improving older driver knowledge and self-awareness through self-assessment: the driving decisions workbook

PURPOSE: This study aims to assess whether the Driving Decisions Workbook, a self-assessment instrument for older drivers, increased self-awareness and general knowledge. This study also assessed perceptions regarding its usefulness, particularly as a tool for facilitating discussions within families of older drivers. A secondary purpose of the study was to determine if problems identified by drivers in the workbook related to problems they had with actual driving. DESIGN AND METHODS: The Driving Decisions Workbook was administered along with a questionnaire and a road test. A convenience sample of 99 licensed drivers aged 65 and above was used. RESULTS: After completing the workbook, about three fourths of the participants reported being more aware of changes that could affect driving. Fourteen percent reported that they had discovered a change in themselves of which they had not been previously aware. All respondents found the workbook to be at least a little useful and thought the workbook could help facilitate family discussions. Workbook responses were positively correlated with overall road test scores. Significant correlations were also noted between the road test and a majority of workbook subsection responses. IMPLICATIONS: This study indicates that the workbook may be a useful first-tier assessment instrument and educational tool for the older driver. It may encourage an older driver to drive more safely and/or to seek clinical assessment, and help in facilitating discussions about driving within their families.     

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。     

On-road and simulated driving: concurrent and discriminant validation

Introduction

A converging pair of studies investigated the validity of a simulator for measuring driving performance/skill.

Study 1

A concurrent validity study compared novice driver performance during an on-road driving test with their performance on a comparable simulated driving test.

Results

Results showed a reasonable degree of concordance in terms of the distribution of driving errors on-road and errors on the simulator. Moreover, there was a significant relationship between the two when driver performance was rank ordered according to errors, further establishing the relative validity of the simulator. However, specific driving errors on the two tasks were not closely related suggesting that absolute validity could not be established and that overall performance is needed to establish the level of skill.

Study 2

A discriminant validity study compared driving performance on the simulator across three groups of drivers who differ in their level of experience - a group of true beginners who had no driving experience, a group of novice drivers who had completed driver education and had a learner's permit, and a group of fully licensed, experienced drivers.

Results

The findings showed significant differences among the groups in the expected direction -- the various measures of driving errors showed that beginners performed worse than novice drivers and that experienced drivers had the fewest errors. Collectively, the results of the concurrent and discriminant validity studies support the use of the simulator as a valid measure of driving performance for research purposes.

Impact on industry

These findings support the use of a driving simulator as a valid measure of driving performance for research purposes. Future research should continue to examine validity between on-road driving performance and performance on a driving simulator and the use of simulated driving tests in the evaluation of driver education/training programs.     

驾驶行为特性与人格特征关系研究

为了开展驾驶行为特性与人格特征关系的研究,选用26名被试人员,运用自主研 发的驾驶员综合能力测试系统,利用数理统计规律,研究被试者复杂反应、速度估计与 人格特征之间的关系。结果表明:在相同的试验环境下,所有被试者在伴有蜂鸣声时复 杂反应错误次数明显多于无蜂鸣声时;男女驾驶员在复杂反应时间方面表现出显著性差 异, 而在复杂反应错误次数方面未表现出明显差异;男女驾驶员在速度估计方面未表现 出显著性差异,但部分驾驶员表现出过高或过低估计速度的倾向;复杂反应指数和速度 估计指数与驾驶员的攻击性、独立性和敢为性之间存在着较强的正相关性,与社会向性 、稳定性之间存在着较强的负相关性;男性驾驶员表现出较强的攻击性、敢为性和独立 性,而女性驾驶员表现出较强的稳定性和社会向性。自主研发的系统能有效地分析了驾 驶行为特性与人格特征之间的内在关系,可以检测出潜在的事故倾向性大的驾驶员,有 利于减少交通事故的发生。     

Identification of aggressive driving from naturalistic data in car-following situations

Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway

Introduction: An improper driving strategy is one of the causative factors for a high probability of runoff and overturning crashes along the horizontal curves of two-lane highways. The socio-demographic and driving experience factors of a driver do influence driving strategy. Hence, this paper explored the effect of these factors on the driver’s runoff risk along the horizontal curves. Method: The driving performance data of 48 drivers along 52 horizontal curves was recorded in a fixed-base driving simulator. The driving performance index was estimated from the weighted lateral acceleration profile of each driver along a horizontal curve. It was clustered and compared with the actual runoff events observed during the experiment. It yielded high, moderate, and low-risk clusters. Using cross-tabulation, each risk cluster was compared with the socio-demographic and experience factors. Further, generalized mixed logistic regression models were developed to predict the high-risk and high to moderate risk events. Results: The age and experience of drivers are the influencing factors for runoff crash. The high-risk event percentage for mid-age drivers decreases with an increase in driving experience. For younger drivers, it increases initially but decreases afterwards. The generalized mixed logistic regression models identified young drivers with mid and high experience and mid-age drivers with low-experience as the high-risk groups. Conclusions: The proposed index parameter is effective in identifying the risk associated with horizontal curves. Driver training program focusing on the horizontal curve negotiation skills and graduated driver licensing could help the high-risk groups. Practical applications: The proposed index parameter can evaluate driving behavior at the horizontal curves. Driving behavior of high-risk groups could be considered in highway geometric design. Motor-vehicle agencies, advanced driver assistance systems manufacturers, and insurance agencies can use proposed index parameter to identify the high-risk drivers for their perusal.     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Driving circumstances and accidents among novice drivers

OBJECTIVE: The study evaluated the accident risk of certain driving circumstances and driving motives among novice drivers. METHODS: Self-reported exposure and accidents according to driving circumstances and driving motives were compared between young (n = 6,847) and middle-aged (n = 942) male and female novice drivers. For young drivers, self-reported accidents were further compared to fatal accidents (n = 645) in terms of the driving conditions in which they occurred. The survey was conducted in 2002 and the questions regarding the quantity and quality of driving exposure and accidents covered the first four years of the novice drivers' driving career after licensing. Data on fatal accidents related to the period of 1990 to 2000. RESULTS: Leisure-time driving, driving just for fun, and driving with passengers and during evenings and at night was more typical for young drivers than for middle-aged drivers. For middle-aged drivers, the most typical driving was driving to or from work. Driving on errands was more typical for females than males. Nighttime driving was overrepresented in young drivers' self-reported and fatal accidents, compared to the share of young drivers' driving at night. Slippery road conditions were over-represented in young male drivers' self-reported accidents, but not in their fatal accidents, whereas for young females slippery road conditions seemed to increase the propensity of fatal accidents. CONCLUSIONS: The study concluded that some driving conditions increase the risk of certain types of accidents among certain driver groups, but not among all drivers. For example, slippery road conditions were overrepresented in young male drivers' minor (self-reported) accidents, but not in their fatal accidents. For young female drivers slippery road conditions seem to increase the propensity of fatal accidents. Driving circumstances are different in minor (self-reported) and fatal accidents. When drawing conclusions regarding accident risk, it is important to determine the seriousness of the accidents which take place.