Driver Skill Research Articles

Hazard perception skills of young drivers with Attention Deficit Hyperactivity Disorder (ADHD) can be improved with computer based driver training: An exploratory randomised controlled trial

BackgroundYoung drivers with Attention Deficit Hyperactivity Disorder (ADHD) are at higher risk of road traffic injuries than their peers. Increased risk correlates with poor hazard perception skill. Few studies have investigated hazard perception training using computer technology with this group of drivers. Objectives*Determine the presence and magnitude of the between-group and within- subject change in hazard perception skills in young drivers with ADHD who receive Drive Smart training. *Determine whether training-facilitated change in hazard perception is maintained over time. MethodsThis was a feasibility study, randomised control trial conducted in Australia. The design included a delayed treatment for the control group. Twenty-five drivers with a diagnosis of ADHD were randomised to the Immediate Intervention or Delayed Intervention group.The Immediate Intervention group received a training session using a computer application entitled Drive Smart. The Delayed Intervention group watched a documentary video initially (control condition), followed by the Drive Smart computer training session. The participant’s hazard perception skill was measured using the Hazard Perception Test (HPT). FindingsAfter adjusting for baseline scores, there was a significant betweengroup difference in post-intervention HPT change scores in favour of the Immediate Intervention group. The magnitude of the effect was large. There was no significant within-group delayed intervention effect. A significant maintenance effect was found at 6-week follow-up for the Immediate Intervention group. ConclusionsThe hazard perception skills of participants improved following training with large effect size and some maintenance of gain. A multimodal approach to training is indicated to facilitate maintenance. A full-scale trial is feasible.

A real-time, MPC-based Motion Cueing Algorithm with Look-Ahead and driver characterization

The use of dynamic driving simulators is nowadays common practice in the automotive industry. The effectiveness of such devices is strongly related to their capabilities of well reproducing the driving sensations, hence it is crucial that the motion control strategies generate both realistic and feasible inputs to the platform. Such strategies are called Motion Cueing Algorithms (MCAs). Model Predictive Control (MPC) has been successfully applied to MCAs, being well suited to solve constrained optimal control problems. However, the predictive aspect of the algorithm has not been exploited effectively yet, mainly due to the hard real-time requirement when using a significantly long prediction window. In this paper, a real time implementation of the so called Look-Ahead (LA) strategy is presented, that is based on an effective manipulation of the reference along the prediction horizon, and on an on-line switching policy to a Non-Look-Ahead strategy when the expected driver behavior is not reliable. An optimal tuning of the MCA is computed by means of a multi-objective optimization, where both performance improvement due to the prediction exploitation, and robustness to varying driver behavior are taken into account. Finally, a characterization of the driver skill level is proposed and validated in experimental environment.

OVERVIEW OF SELECTED HYDRAULIC DEVICES SUPPORTING ROAD RESCUE OPERATIONS

The intense human activity determines the continuous development of systems and means of transport, which contributes to the intensification of existing road traffic risks and the emergence of new ones. Reduction in the number of fatalities of road accidents is dependent on investment in transport infrastructure, the development of safety sys-tems for means of transport and the care for the technical condition of vehicles. Fur-thermore, the human factor is manifested in the growing awareness of hazards and im-proving skills of vehicle drivers. The article presents the construction, operating principles and technical capabilities of the most commonly used hydraulic rescue tools. All this was presented against the background of selected problems occurring during rescue opera-tions while releasing victims caught in car wrecks.

How Do Platform Participants Respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform Using a Quasi-Experiment

Online rating systems can lead, on occasion, to reviews that are unfair or unrepresentative of the true quality provided. On the one hand, receiving an unfairly low rating once, might induce participants to exert more effort and receive a better rating the next time. On the other hand, it might dispirit participants and make them exert less effort. We use data from a ride-sharing platform in India where driver ratings were made particularly salient to the driver after each trip. Our data suggests that if a customer experiences a ride cancellation, they are more likely to unfairly blame the replacement driver. We use this as a exogenous source of unfair negative ratings for the driver. We show that drivers are more likely to respond negatively to a bad rating and receive subsequently bad ratings if they were blameless for the previous negative rating. This effect is larger in contexts where there is a higher potential for an emotional response and when there is a greater need for driver skill in the subsequent ride. These unfair ratings can lead drivers to leave the platform, suggesting a broader negative effect of unfair negative ratings on platform participation.

Simulated Driving Skills Evaluation of Teenagers With Attention Deficit Hyperactivity Disorder Before Driving Lessons

We evaluated the driving skills of teenagers with attention deficit hyperactivity disorder (ADHD) during simulated driving before starting driving lessons and observed whether methylphenidate (MPH) affected their performance. Sixty teenagers ages 15-18 yr were included; 29 teenagers with ADHD were tested with and without MPH, and 31 teenagers (control group) were tested once. All participants were tested on the STISIM Drive™ simulator. The number of center-line crossings was higher in the group without MPH treatment than in the control group and the MPH-treated group. The group without MPH treatment had more road-edge excursions compared with the control group and drove faster than the MPH-treated group. Adolescents with ADHD without MPH treatment demonstrated impaired performance more often while driving the simulator, resembling characteristics found during on-road driving among teenagers with ADHD. Trainer awareness is a primary intervention before taking driving lessons to help teenagers achieve safe driving performance.

Validation of the German version of the Driver Skill Inventory (DSI) and the Driver Social Desirability Scales (DSDS)

The psychometric properties of the new German versions of the Driver Skill Inventory (DSI) and the Driver Social Desirability Scales (DSDS) were examined. The DSI is a self-report measure assessing perceptual-motor skills and the safety motive as two important aspects of driving behavior. Self-report measures, however, are susceptible to socially desirable responding (SDR) which is why both general and specific driving-related SDR scales have been developed: Based on the Balanced Inventory of Desirable Responding (BIDR), the DSDS taps Driver Impression Management and Driver Self-Deception as two important aspects of SDR. In two validation studies with less experienced (N=130) and experienced drivers (N=1199), both inventories showed the expected two-factor structure and satisfactory internal consistency. In Study 1, self-ratings were compared with and confirmed by peer-ratings. In both studies, we accumulated evidence of convergent and discriminant validity for the German version of the DSI by correlating it with demographic, driving-specific, and personality measures, including the Big Five, Type A behavior, and sensation seeking. The DSI seemed to be only marginally contaminated by SDR.

How Do Platform Participants Respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform Using a Quasi-Experiment

Online rating systems can lead, on occasion, to reviews that are unfair or unrepresentative of the true quality provided. On the one hand, receiving an unfairly low rating once, might induce someone a platform supplier to exert more effort and receive a better rating the next time. On the other hand, it might dispirit suppliers and make them exert less effort. We use data from a ride-sharing platform in India where driver ratings were made particularly salient to the driver after each trip. Our data suggests that if a customer experiences a ride cancellation, they are more likely to unfairly blame the replacement driver. We use this as a exogenous source of unfair negative ratings for the driver. We show that drivers are more likely to respond negatively to a bad rating and receive subsequently bad ratings if they were blameless for the previous negative rating. This effect is larger in contexts where there is a higher potential for an emotional response and when there is a greater need for driver skill in the subsequent ride.

Review on Operational Performance of Employee Shuttle Service in Industrial Areas of Jababeka-1 Cikarang, West Java

Bekasi has one of the biggest industrial areas in Indonesia called Industrial Area of Jababeka 1 Cikarang, which has provided facility of employee “shuttle” transport for the employees. However, the employee shuttle service has not been able to accommodate all employees in the industrial areas especially in Industrial Area of Jababeka 1 Cikarang. This study aims to investigate the existing condition of operational performance of employee shuttle service, knowing the satisfaction and the necessity level of the service based on users’ perception, and provides recommendation for the improvement of employee shuttle service in the Industrial Area of Jababeka 1 Cikarang. This study uses Importance Performance Analysis (IPA) method and multiple linear regression models. The final regression model is Y = 2.034 + 1.621X 2 + 1.039X 4 + 1.311X 5 + 0.829 X 6 + 1.046X 7 + 1.877X 8 + 1.619X 10 . This results shows that there are 3 variables which influence the performance of employee shuttle service (R 2 = 0. 934) including X 8 variable (Sanitary Facility/Dust Bin) and X 2 variable (Vehicle Driving Skills), and X 10 variable (Age of the Vehicle).

Simultaneous Achievement of Workload Reduction and Skill Enhancement in Backward Parking by Haptic Guidance

Advanced driver assistance systems (ADASs) have been developed and have subsequently decreased opportunities for driver skill development because of degraded situational awareness and less activity in the control loop. Beginning drivers must therefore engage in training. The idea has arisen that haptic shared control, which encourages a driver to operate the vehicle properly and with correct timing, should serve as a training system for daily driving. Such a system, however, might degrade performance, comfort, or safety because training aspects might increase the driver workload as a result of error correction feedback. The possibility of lowered usability is not acceptable for ADASs. This study was conducted to develop an assist system that achieves workload reduction and skill improvement. A haptic assistance system that applies guidance torque on the steering wheel was proposed and investigated for backward parking, which is a difficult driving situation. Driving simulator experiments were conducted. Results showed that both support and after-use effects were realized. This study provides knowledge for the development of driving systems using haptic assistant systems for which initial skill influences performance.

How indicative is a self-reported driving behaviour profile of police registered traffic law offences?

Although most motorised countries have experienced massive improvements in road safety over the last decades, human behaviour and differences in accident risk across sub-groups of drivers remains a key issue in the area of road safety. The identification of risk groups requires the identification of reliable predictors of safe or unsafe driving behaviour. Given this background, the aim of this study was to test whether driver sub-groups identified based on self-reported driving behaviour and skill differed in registered traffic law offences and accidents, and whether group membership was predictive of having traffic law offences. Sub-groups of drivers were identified based on the Driver Behaviour Questionnaire (DBQ) and the Driver Skill Inventory (DSI), while traffic offences and accidents were register-based (Statistics Denmark). The participants (N=3683) were aged 18–84 years and randomly selected from the Danish Driving License Register. Results show that the driver sub-groups differed significantly in registered traffic offences but not in registered accidents. In a logistic regression analysis, the sub-group “Violating unsafe drivers” was found predictive of having a traffic offence, even when socio-demographic variables and exposure were controlled for. The most important predictive factor, however, was having a criminal record for non-traffic offences, while gender, living without a partner, and being self-employed also had a significant effect. The study confirms the use of the DBQ and DSI as suitable instruments for predicting traffic offences while also confirming previous results on accumulation of problematic behaviours across life contexts. The finding that driver sub-groups did not differ in registered accidents supports the recent research activities in finding and modelling surrogate safety measures.

Driver behaviour detection and vehicle rating using multi-UAV coordinated vehicular networks

Road accidents account for more than 2% of the total deaths across the globe with more than a million deaths each year due to road mishaps and improper traffic management. Traffic management is a major problem faced by modern cities due to a large number of vehicles operating at the same time. One of the major issues for road mishaps is driver's behaviour and skills. Thus, tracking vehicles and analyzing the driver behaviour is required for proper regulation of traffic. Some of the solutions are provided using infrastructure-based vehicular ad hoc networks (VANETs). However, their operations are constrained by the traffic itself, thus, limiting their scope. A new solution by forming VANETs using multiple unmanned aerial vehicles (UAVs) is proposed which is independent of using road side units (RSUs) for communications. The proposed approach is analyzed using simulations as well as real-time dataset.

Does early training improve driving skills of young novice French drivers?

The aim of this research was to study drivers’ performances and divided attention depending on their initial training. The performances of young novice drivers who received early training, traditionally trained drivers and more experienced drivers were compared during a dual task consisting of a simulated car-following task and a number’ parity judgment task. It was expected that, due to their limited driving experience, the young novice drivers would have more difficulty in adequately distributing their attention between the two tasks. Poorer performances by novice drivers than experienced drivers were therefore expected. The results indicate that traditionally trained drivers had more difficulties in speed regulation and maintaining their position in the lane than drivers with early training and experienced drivers. Performance impairment linked to driving inexperience was also found in the secondary task. The results were interpreted regarding the attentional resources involved in driving with a secondary task and supported the positive effects of French early training.

Driving skill classification in curve driving scenes using machine learning

Driver support and infotainment systems can be adapted to the specific needs of individual drivers by assessing driver skill and state. In this paper, we present a machine learning approach to classifying the skill at maneuvering by drivers using both longitudinal and lateral controls in a vehicle. Conceptually, a model of drivers is constructed on the basis of sensor data related to the driving environment, the drivers’ behaviors, and the vehicles’ responses to the environment and behavior together. Once the model is built, the driving skills of an unknown driver can be classified automatically from the driving data. In this paper, we demonstrate the feasibility of using the proposed method to assess driving skill from the results of a driving simulator. We experiment with curve driving scenes, using both full curve and segmented curve scenarios. Six curves with different radii and angular changes were set up for the experiment. In the full curve driving scene, principal component analysis and a support vector machine-based method accurately classified drivers in 95.7 % of cases when using driving data about high- and low/average-skilled driver groups. In the cases with segmented curves, classification accuracy was 89 %.

An Engineering or Behavioural Approach? A Study into Employees’ Perceptions Regarding the Effectiveness of Occupational Road Safety Initiatives

Background and Aims: Considerable variation has been documented with fleet safety interventions’ abilities to create lasting behavioural change, and research has neglected to consider employees’ perceptions regarding the effectiveness of fleet interventions. This is a critical oversight as employees’ beliefs and acceptance levels (as well as the perceived organisational commitment to safety) can ultimately influence levels of effectiveness, and this study aimed to examine such perceptions in Australian fleet settings. Method: 679 employees sourced from four Australian organisations completed a safety climate questionnaire as well as provided perspectives about the effectiveness of 35 different safety initiatives. Results: Countermeasures that were perceived as most effective were a mix of human and engineering-based approaches: (a) purchasing safer vehicles; (b) investigating serious vehicle incidents; and (c) practical driver skills training. In contrast, least effective countermeasures were considered to be: (a) signing a promise card; (b) advertising a company’s phone number on the back of cars for complaints and compliments; and (c) communicating cost benefits of road safety to employees. No significant differences in employee perceptions were identified based on age, gender, employees’ self-reported crash involvement or employees’ self-reported traffic infringement history. Perceptions of safety climate were identified to be “moderate” but were not linked to self-reported crash or traffic infringement history. However, higher levels of safety climate were positively correlated with perceived effectiveness of some interventions. Conclusion: Taken together, employees believed occupational road safety risks could best be managed by the employer by implementing a combination of engineering and human resource initiatives to enhance road safety. This paper will further outline the key findings in regards to practice as well as provide direction for future research.

Identification of contributing factors for wrong-way crashes on freeways in Illinois

ABSTRACTTo investigate the contributing factors for wrong-way crashes on freeways based on information available from crash databases and crash reports, causal tables and a Haddon matrix are used to analyze fatal and injury-related crashes caused by wrong-way driving from 2004 to 2009 in Illinois. For the first step, causal tables are generated based on the police crash reports, in which the percentage of crashes caused by each factor is calculated. Based on these percentages, the contributing factors are ranked. Next, a Haddon matrix is developed for each wrong-way crash in which different factors are identified separately for periods before, during, and after the crash. These factors include drivers' age, drivers' condition, crash causes, vehicle types, vehicle maneuvers, roadway conditions, weather, and wrong-way entry points. For a crash with multiple contributing factors, a weighted point is calculated and assigned to each factor. The total points for each factor are used to rank the order of all contributing factors. Furthermore, a significance test is used to analyze the statistical significance of each of those factors. The analysis results indicate that alcohol impairment, darkness, and driver's age and skill are among the top contributing factors for wrong-way crashes.

Evaluation of Training Interventions to Mitigate Effects of Fatigue and Sleepiness on Driving Performance

Fatigue and sleepiness are leading contributors to road crashes. Either can occur in the evening, sometime around 10:00 p.m., after a day that begins in the morning, sometime around 8:00 a.m. Other factors contribute as well to performance decrements in the evening for those who regularly work during the day. It is arguably the case that these various factors are responsible for the observed decrements in safety-critical driving skills, such as hazard anticipation, hazard mitigation, and attention maintenance, which occur in the evening. However, it is by no means clear whether a training program can be designed to mitigate the effects that such factors have on these critical driving skills. A simulator experiment was undertaken to determine whether a training program [sleepiness and fatigue evaluation training (SAFE-T)] could lead to improvements in the hazard anticipation, hazard mitigation, and attention maintenance skills of drivers who had been awake for 12 h. The results showed that for all three skills trained drivers performed significantly better during the posttest (after SAFE-T) than the pretest (before SAFE-T), whereas the placebo drivers performed significantly worse during the posttest than the pretest. Fatigue and sleepiness both increased during the posttest from their pretest values. Thus the effects of training are still observed even in the presence of increases in fatigue and sleepiness.

Satisficing Curve Negotiation: Explaining Drivers’ Situated Lateral Position Variability

Abstract: Drivers exhibit a range of lateral positions that depend on their location down the road in relationship to the curves. For example, within a curve the range is narrower and biased towards the inner road edge compared to straight sections where it is more centralized and wider. The question is what shapes the swath of lateral positions that drivers accept. It is generally accepted that drivers under normal conditions (i.e. not race car drivers) are satisficing controllers rather than optimizing controllers that operate based on a number of aspiration levels that they try to protect. In this paper, lower bounds on straight and curved time to line crossing (TLC) are hypothesized as aspiration levels that determine the acceptable range of lateral offsets. These lower TLC bounds also shape the speed at which a curve can be taken because when the aspiration levels cannot be reached at the current speed, a slower speed needs to be adopted to maintain sufficiently high straight and/or curved TLCs. This paper provides a theoretical exposition of straight and curved TLC as a function of environmental and driver skill factors. It provides much evidence that TLC plays a role in mediating drivers’ lateral position and speed choices.

Can the monitoring of animal welfare parameters predict pork meat quality variation through the supply chain (from farm to slaughter)?

The objective of this study was to assess the relationship between the animal welfare conditions evaluated through the supply chain and pork quality variation. A total of 4,680 pigs from 12 farms-5 animal welfare improved raising system (AWIRS) and 7 conventional raising system (CON) farms-were assessed from farm to slaughter through a comprehensive audit protocol merging the European Welfare Quality, the Canadian Animal Care Assessment, and American Meat Institute audit guide criteria. At the abattoir, a subsample of 1,440 pigs (120 pigs/farm) was randomly chosen out of 24 loads (2 farms per wk) transported by 2 drivers (driver A and driver B) for the assessment of stunning effectiveness, carcass bruises, blood lactate levels, and meat quality traits. Meat quality was assessed in the longissimus lumborum (LL) muscle 24 h postmortem by measuring ultimate pH (pHu), color (L*, a*, and b*), and drip loss. Data were analyzed by the MIXED, GLIMMIX, and NAPAR1WAY procedures of SAS. Spearman correlations were calculated to determine the relationship between audit scores and meat quality traits. Better animal welfare conditions, as showed by greater final scores for good housing (GHo; = 0.001) and good health ( = 0.006) principles, were recorded at AWIRS farms. Pigs from AWIRS farms handled by driver B displayed a greater percentage of turning back ( = 0.01) and slips ( < 0.001) during unloading and a greater ( = 0.02) frequency of falls in the stunning chute. A greater ( = 0.02) reluctance to move at loading was found in CON pigs loaded by driver A compared with driver B, whereas a greater ( < 0.001) reluctance to move was found in these pigs at unloading when they were unloaded by driver B. Drip loss was higher ( = 0.003) and pale, soft, and exudative pork percentage was greater ( < 0.001) in the LL muscle of the heavier AWIRS pigs. The GHO principle was best correlated with pHu ( = -0.75, = 0.01) and Minolta L* value ( = 0.87, < 0.001) of the LL muscle. Overall, drip loss variation in the LL muscle was correlated with the frequency of slips at unloading ( = 0.63, = 0.001) and in the restrainer area ( = 0.74, < 0.001). The results of this study showed that the quality of the raising system and truck driver skills as assessed by animal welfare audit protocols are important sources of variation in the behavioral response of pigs to preslaughter handling and may affect pork quality variation. However, the different live weight between CON and AWIRS pigs may have biased the meat quality results in this study.

Effect of First Aid Education on First Aid Knowledge and Skills of Commercial Drivers in South West Nigeria.

Prompt prehospital care is essential for improving outcomes of road crash victims; however, this service is sub-optimal in developing countries because Emergency Medical Services (EMS) are not readily available. Training of lay responders in first aid has been suggested as a means of filling this gap in settings with inadequate EMS. This study was conducted to determine the effect of first aid training on the first aid knowledge and skills of commercial drivers. A before-and-after study was conducted among 128 commercial drivers (62 intervention and 66 controls) selected by multi-stage sampling. Drivers' first aid knowledge and skills were assessed at baseline, immediate, and three months post-intervention. The intervention involved a 2-day training session in first aid. Repeated measures ANOVA was used to test for differences in respondents' pre- and post-intervention scores over the three assessment points. Mean first aid knowledge scores for intervention drivers were 48.9% (SD=12.0), 57.8% (SD=11.2), and 59.2% (SD=9.0) at baseline, immediate, and three months post-intervention. Corresponding scores for the controls were 48.3% (SD=12.8), 39.2% (SD=15.3), and 46.8% (SD=15.3). Mean first aid skill scores for intervention drivers were 17.5% (SD=3.8), 80.7% (SD=8.3), and 72.3% (SD=16.8). Scores for control drivers were 16.5% (SD=4.5), 16.3% (SD=4.7), and 20.4% (SD=9.1), respectively. Repeated measures ANOVA showed significant differences in first aid knowledge and skills scores over the three phases. Independent t-test revealed significant differences in scores between the intervention and control groups post-intervention. The training led to significant improvement in first aid knowledge and skills of intervention drivers. This confirms that lay responders can be trained in provision of first aid. The slight drop in skills scores, which occurred three months post-intervention, highlights the need for periodic refresher trainings to be conducted for the drivers in order to maintain the knowledge and skills acquired.

Hazard prediction discriminates between novice and experienced drivers

Typical hazard perception tests often confound multiple processes in their responses. The current study tested hazard prediction in isolation to assess whether this component can discriminate between novice and experienced drivers. A variant of the hazard perception test, based on the Situation Awareness Global Assessment Technique, found experienced drivers to outperform novices across three experiments suggesting that the act of predicting an imminent hazard is a crucial part of the hazard-perception process. Furthermore three additional hypotheses were tested in these experiments. First, performance was compared across clips of different length. There was marginal evidence that novice drivers’ performance suffered with the longest clips, but experienced drivers’ performance did not, suggesting that experienced drivers find hazard prediction less effortful. Secondly, predictive accuracy was found to be dependent on the temporal proximity of visual precursors to the hazard. Thirdly the relationship between the hazard and its precursor was found to be important, with less obvious precursors improving the discrimination between novice and experience drivers. These findings demonstrate that a measure of hazard prediction, which is less confounded by the influence of risk appraisal than simple response time measures, can still discriminate between novice and experienced drivers. Application of this methodology under different conditions can produce insights into the underlying processes that may be at work, whilst also providing an alternative test of driver skill in relation to the detection of hazards.