Errors and violations on the roads: a real distinction?

In considering the human contribution to accidents, it seems necessary to make a distinction between errors and violations; two forms of aberration which may have different psychological origins and demand different modes of remediation. The present study investigated whether this distinction was justified for self-reported driver behaviour. Five hundred and twenty drivers completed a driver behaviour questionnaire (DBQ) which asked them to judge the frequency with which they committed various types of errors and violations when driving. Three fairly robust factors were identified: violations, dangerous errors, and relatively harmless lapses, respectively. Violations declined with age, errors did not. Men of all ages reported more violations than women. Women, however, were significantly more prone to harmless lapses (or more honest) than men. These findings were consistent with the view that errors and violations are indeed mediated by different psychological mechanisms. Violations require explanation in terms of social and motivational factors, whereas errors (slips, lapses, and mistakes) may be accounted for by reference to the information-processing characteristics of the individual.     

Driving errors,driving violations and accident involvement

Abstract

A survey of over 1600 drivers is reported, the results of which are consistent with those reported in an earlier study (Reason et al. 1990), which identified a three-fold typology of aberrant driving behaviours. The first type, lapses, are absent-minded behaviours with consequences mainly for the perpetrator, posing no threat to other road users. The second type, errors, are typically misjudgements and failures of observation that may be hazardous to others. The third type, violations, involve deliberate contraventions of safe driving practice. In the present study the survey instrument used, the Driver Behaviour Questionnaire, was also shown to be reliable over time. Each type of behaviour was found to have different demographic correlates. Most importantly, accident liability was predicted by self-reported tendency to commit violations, but not by tendency to make errors or to have lapses. The implications for road safety are discussed.     

Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.     

Car driver speed choice in Scotland

Drivers who commit driving violations, such as speeding, crash more. Driving violations reduce safety margins amplifying the impact of driver errors. Speed is placed in the context of car use and its attractions. It is argued that speed choice results from the interaction of opportunities, obligations and inclinations. Data from large-scale surveys of Scottish car drivers support this and show that many drivers in Scotland prefer to drive at or below the speed limit and that many say they are currently cutting their normal driving speed. Suggestions for promoting safer and more sustainable speed choices are made.     

Effects of an in-vehicle collision avoidance warning system on short- and long-term driving performance

Many new in-vehicle systems focus on accident prevention by facilitating the driving task. One such driving aid is an in-vehicle collision avoidance warning system (IVCAWS), used to alert the driver to an impending collision. Our study evaluated the effects of an imperfect IVCAWS both on driver headway maintenance and on driver behavior in response to warning system errors. Our results showed that drivers tend to overestimate their headway and consequently drive with short and potentially dangerous headways, and that IVCAWSs are a useful tool for educating drivers to estimate headway more accurately. Moreover, our study showed that after a relatively short exposure to the system, drivers were able to maintain longer and safer headways for at least six months. The practical implications of these results are that the use of an IVCAWS should be considered for inclusion in driver education and training programs.     

Drivers' margins of safety considered as a focus for research on error

Accident statistics alone cannot provide a sound understanding of driver error, although they can assist the evaluation of remedial measures against errors and accidents. Roadside observation of drivers' errors can provide a valid index of their relative riskiness and of overall accident frequency, but only in route-specific applications. Field testing of hypotheses developed from theories of driver error is seen to be a far more valid and arguably more cost-effective method of improving road safety than relying on post hoc subjective assessments of error contributions to accident statistics. The distinction between driving task and envronmental factors which contribute to error production and those which constrain error correction is not well-documented in road accident studies. Yet it seems essential to make this distinction if we are to reach a sound understanding of research requirements in this field and hence identify and evaluate cost effective countermeasures against driver error. The bias which certain drivers appear to have towards inadequate safety margins is seen to provide an instructive theoretical framework for field studies of error production and error correction as contributory factors in traffic accident causation.     

Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.     

The design of next generation in-vehicle navigation systems for the older driver

It has been proposed that the current design of in-vehicle displays may not be appropriate for the older driver. This paper describes an empirical, road-based investigation of the benefits to older and younger drivers of providing landmarks within the instructions presented by an in-vehicle navigation system. Thirty two participants navigated a challenging urban route using either landmarks or distance information to identify the location of forthcoming manoeuvres. A range of driver behaviour measures were collected, including visual glance data, driving errors, driver workload, navigation errors, navigation confidence, and pre and post-trial driver attitudinal responses. Results show that, for older and younger drivers, landmarks reduced the time spent glancing to a visual display, reduced navigation and driving errors, and influenced driver confidence. There were some key differences between the older and younger drivers. The wider implications for the design of in-car interfaces for the older driver are discussed.     

Effects of advertising billboards during simulated driving

There is currently a great deal of interest in the problem of driver distraction. Most research focuses on distractions from inside the vehicle, but drivers can also be distracted by objects outside the vehicle. Major roads are increasingly becoming sites for advertising billboards, and there is little research on the potential effects of this advertising on driving performance. The driving simulator experiment presented here examines the effects of billboards on drivers, including older and inexperienced drivers who may be more vulnerable to distractions. The presence of billboards changed drivers’ patterns of visual attention, increased the amount of time needed for drivers to respond to road signs, and increased the number of errors in this driving task.     

Relationships between driving simulator performance and driving test results

This article is considered relevant because: 1) car driving is an everyday and safety-critical task; 2) simulators are used to an increasing extent for driver training (related topics: training, virtual reality, human – machine interaction); 3) the article addresses relationships between performance in the simulator and driving test results–a relevant topic for those involved in driver training and the virtual reality industries; 4) this article provides new insights about individual differences in young drivers' behaviour. Simulators are being used to an increasing extent for driver training, allowing for the possibility of collecting objective data on driver proficiency under standardised conditions. However, relatively little is known about how learner drivers' simulator measures relate to on-road driving. This study proposes a theoretical framework that quantifies driver proficiency in terms of speed of task execution, violations and errors. This study investigated the relationships between these three measures of learner drivers' (n = 804) proficiency during initial simulation-based training and the result of the driving test on the road, occurring an average of 6 months later. A higher chance of passing the driving test the first time was associated with making fewer steering errors on the simulator and could be predicted in regression analysis with a correlation of 0.18. Additionally, in accordance with the theoretical framework, a shorter duration of on-road training corresponded with faster task execution, fewer violations and fewer steering errors (predictive correlation 0.45). It is recommended that researchers conduct more large-scale studies into the reliability and validity of simulator measures and on-road driving tests.     

Errors in routine driving tasks: a model and proposed analysis technique

Abstract

Models of behaviour and cognitive errors are briefly reviewed. A model derived from the work of Reason and Rasmussen is applied to the analysis of accidents at a crossroad in Friesland where the bulk of accidents occurred to drivers familiar with the location. Detailed application of the predicted error mechanisms to the steps of the driving task allows testable hypotheses to be formulated to differentiate between a number of possible causes of the accidents. The implications for research into accidents during routine driving tasks are discussed.     

Interpersonal violations,speeding violations and their relation to accident involvement in Finland

The aim of the present study was to replicate the distinction between errors, lapses and violations, and to identify aggressive violations from normal or highway code violations. Furthermore, the relationship of these behaviours with road traffic accidents was examined. A total number of 1126 Finnish drivers completed a questionnaire containing the Driver Behaviour Questionnaire (DBQ) with extended violations scale, and questions regarding background information, such as age, gender and mileage. Also, questions about previous accidents and fines were asked. Factor analysis showed that a four-factor structure seemed more appropriate than the earlier established three-factor structure. The four factors were errors, lapses, speeding violations and interpersonal violations. The two types of violations result from different motives, and seem to be associated with different kinds of affect. Both interpersonal and speeding violations were reported most by young males, which was consistent with earlier findings. Logistic regression analyses indicated that errors predicted active accident involvement after partialling out the effects of demographic variables, whereas interpersonal violations were positively related to involvement in passive accidents. This was presumably due to different reporting tendencies of respondents. Speeding tickets were predicted by speeding and interpersonal violations and lapses and penalties for speeding by both kinds of violations and errors. Penalties for speeding, parking and other offences were predicted by interpersonal violations. The implications of these results are discussed.     

Interpersonal violations,speeding violations and their relation to accident involvement in Finland

The aim of the present study was to replicate the distinction between errors, lapses and violations, and to identify aggressive violations from normal or highway code violations. Furthermore, the relationship of these behaviours with road traffic accidents was examined. A total number of 1126 Finnish drivers completed a questionnaire containing the Driver Behaviour Questionnaire (DBQ) with extended violations scale, and questions regarding background information, such as age, gender and mileage. Also, questions about previous accidents and fines were asked. Factor analysis showed that a four-factor structure seemed more appropriate than the earlier established three-factor structure. The four factors were errors, lapses, speeding violations and interpersonal violations. The two types of violations result from different motives, and seem to be associated with different kinds of affect. Both interpersonal and speeding violations were reported most by young males, which was consistent with earlier findings. Logistic regression analyses indicated that errors predicted active accident involvement after partialling out the effects of demographic variables, whereas interpersonal violations were positively related to involvement in passive accidents. This was presumably due to different reporting tendencies of respondents. Speeding tickets were predicted by speeding and interpersonal violations and lapses and penalties for speeding by both kinds of violations and errors. Penalties for speeding, parking and other offences were predicted by interpersonal violations. The implications of these results are discussed.     

An investigation of train driver visual strategies

Train driving is primarily a visual task; train drivers are required to monitor the dynamic scene visually both outside and inside the train cab. Poor performance on this visual task may lead to errors, such as signals passed at danger. It is therefore important to understand the visual strategies that train drivers employ when monitoring and searching the visual scene for key items, such as signals. Prior to this investigation, a pilot study had already been carried out using an eye tracking technique to investigate train drivers’ visual behaviour and to collect data on driver monitoring of the visual environment, Groeger et al. (2003) Pilot study of train drivers’ eye movements, University of Surrey. However, a larger set of data was needed in order to understand more fully train driver visual behaviour and strategies. In light of this need, the Transport Research Laboratory produced a methodology for the assessment of UK train driver visual strategies, on behalf of the Rail Safety and Standards Board and applied this methodology to conduct a large-scale trial. The study collected a wealth of data on train drivers’ visual behaviour with the aim of providing a greater understanding of the strategies adopted. The corneal dark-eye tracking system chosen for these trials tracks human visual search and scanning patterns, and was fitted to 86 drivers whilst driving in-service trains. Data collected include the duration and frequency of glances made towards different elements of the visual scene. In addition, the train drivers were interviewed after driving the routes, to try and understand the thought processes behind the behaviour observed. Statistical analysis of over 600 signal approaches was conducted. This analysis revealed that signal aspect, preceding signal aspect, signal type and signal complexity are important factors, which affect the visual behaviour of train drivers. Train driver interview data revealed that driver expectation also plays a significant role in train driving. The findings of this study have implications for the rail industry in terms of infrastructure design, design of the driving task and driver training. However, train driving is extremely complex and the data from this study only begin to describe and explain train driver visual strategies in the specific context of signal approaches. This study has provided a wealth of data and further analysis of it is needed to investigate the role of other factors and the complex relationships between factors during signal approaches and other driving situations systematically. Finally, there are important aspects of visual behaviour that cannot be examined using these data or this method. Investigation of other aspects of visual behaviour, such as peripheral vision, will require other methods such as simulation.     

Violations and errors during simulation-based driver training

The effectiveness of virtual driving instruction can increase when techniques that automatically distinguish between violations and errors are available, two behaviours requiring different types of remediation. This study reports the analysis of the objectively measured performance of 520 participants completing a simulation-based training programme. Factor analysis of failure reasons showed that violations and errors were the primary underlying factors. Men committed more violations and women made more errors; the magnitude of sex differences corresponded to the factor loadings. Factor analysis of the mean task completion times yielded a factor that can be described as the extent to which motivation for speed resulted in quicker task execution. Quicker participants completed more tasks, committed more violations, but made fewer errors. Participants reduced errors during forced-paced driving and increased speed during self-paced driving. The authors would recommend exploiting the distinction between violations and errors by developing interfaces and feedback for both types of aberration.     

Violations and errors during simulation-based driver training

The effectiveness of virtual driving instruction can increase when techniques that automatically distinguish between violations and errors are available, two behaviours requiring different types of remediation. This study reports the analysis of the objectively measured performance of 520 participants completing a simulation-based training programme. Factor analysis of failure reasons showed that violations and errors were the primary underlying factors. Men committed more violations and women made more errors; the magnitude of sex differences corresponded to the factor loadings. Factor analysis of the mean task completion times yielded a factor that can be described as the extent to which motivation for speed resulted in quicker task execution. Quicker participants completed more tasks, committed more violations, but made fewer errors. Participants reduced errors during forced-paced driving and increased speed during self-paced driving. The authors would recommend exploiting the distinction between violations and errors by developing interfaces and feedback for both types of aberration.     

How do environmental characteristics at intersections change in their relevance for drivers before entering an intersection: analysis of drivers’ gaze and driving behavior in a driving simulator study

Accident studies in Germany found that in about 90 % of intersection accidents, failure to acquire the relevant information of the driving situation was the main reason for drivers’ errors (Vollrath et al. in Ableitung von Anforderungen an Fahrerassistenzsysteme aus Sicht der Verkehrssicherheit. Wirtschaftsverlag NW, Bremerhaven, 2006). Studies of bicycle–car accidents assume that improper attention allocation strategies and unjustified expectations by drivers are important for this kind of error (Räsänen and Summala in Accid Anal Prev 30:657–666, 1998). Aim of the study was to examine the psychological processes of drivers’ attention allocation and driving behavior in different intersection situations varied by two environmental characteristics. A give way T-intersection was varied by (1) low and high traffic density of oncoming cars from the left and (2) number of task-relevant information areas (in addition to the oncoming cars from the left with or without pedestrians on the right). It was examined how these environmental characteristics change in their relevance for drivers while entering the intersections. The analysis was conducted in three intersection epochs (Approaching, Waiting, Accelerating). A total of 40 subjects (26 male, 14 female), ranged in age from 19 to 55 years (M = 31.0 years), participated in the study. The results showed that drivers’ attention allocation (e.g., mean gaze duration) and driving behavior (e.g., waiting time) systematically depends on these environmental characteristics which require different actions of the driver and change in their relevance when entering an intersection. The results support the idea of attention allocation strategies by drivers which are specific for certain driving situations. These findings can support approaches of driver modeling at intersections.     

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers’ violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased.

     

A comparison of the cell phone driver and the drunk driver

OBJECTIVE: The objective of this research was to determine the relative impairment associated with conversing on a cellular telephone while driving. BACKGROUND: Epidemiological evidence suggests that the relative risk of being in a traffic accident while using a cell phone is similar to the hazard associated with driving with a blood alcohol level at the legal limit. The purpose of this research was to provide a direct comparison of the driving performance of a cell phone driver and a drunk driver in a controlled laboratory setting. METHOD: We used a high-fidelity driving simulator to compare the performance of cell phone drivers with drivers who were intoxicated from ethanol (i.e., blood alcohol concentration at 0.08% weight/volume). RESULTS: When drivers were conversing on either a handheld or hands-free cell phone, their braking reactions were delayed and they were involved in more traffic accidents than when they were not conversing on a cell phone. By contrast, when drivers were intoxicated from ethanol they exhibited a more aggressive driving style, following closer to the vehicle immediately in front of them and applying more force while braking. CONCLUSION: When driving conditions and time on task were controlled for, the impairments associated with using a cell phone while driving can be as profound as those associated with driving while drunk. APPLICATION: This research may help to provide guidance for regulation addressing driver distraction caused by cell phone conversations.     

Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts

Abstract

Human Factors Analysis and Classification System (HFACS) is based upon Reason’s organizational model of human error which suggests that there is a ‘one to many’ mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens (HFACS level 1 error and violations). Using accident data derived from 523 military aircraft accidents, the relationship between HFACS level 2 preconditions and level 1 unsafe acts was modelled using an artificial neural network (NN). This allowed an empirical model to be developed congruent with the underlying theory of HFACS. The NN solution produced an average overall classification rate of ca. 74% for all unsafe acts from information derived from their level 2 preconditions. However, the correct classification rate was superior for decision- and skill-based errors, than for perceptual errors and violations.

Practitioner Summary: A model to predict unsafe acts (HFACS level 1) from their preconditions (HFACS level 2) was developed from the analysis of 523 military aircraft accidents using an artificial NN. The results could correctly predict approximately 74% of errors.