Driver Training Research Articles

IDENTIFICATION OF INCONVENIENCES AT TRANSPORT OPERATORS’ WORKPLACES

This article presents the results of a pilot survey of 300 transport operators, such as drivers, train drivers, and rescue workers. The surveys were conducted online using a Google form based on the Computer-Assisted Web Interview (CAWI) method. The following research objectives were set: to identify and compare the most relevant factors affecting the health and wellbeing of transport vehicle operators and to identify the key risks associated with their work. The findings were presented using descriptive statistics and correlation and principal component analyses. Descriptive characteristics indicated which quantitative characteristics were associated with exposure and discomfort. On the other hand, the results of correlation analyses showed, among other things, that “level of rest” as a function of “fatigue” showed a decreasing relationship and that “pain in arms, legs, lower back or neck” depended on “work position,” “use of excessive force,” and “work severity.” The results of the principal component analysis confirmed that the data cluster under the form of factors and that there are factors whose information values are insignificant. A similar conclusion applies to the input data (i.e., the answers to the test questions). The analysis showed that only the answers to 15 of 50 questions exceeded the threshold of 2% of the information entered in the test. This could lead to the conclusion that if the test could be repeated in the future, the correct result might be obtained with slightly fewer test questions.

The influence of gamification and motivational factors on driver engagement in online learning

Gamification of education is a developing approach for increasing motivation and engagement by incorporating game design elements in educational environments. Despite increasing academic research exploring the use of gamification in education little is known about the application of the approach in the context of driver training. This study verified whether the gamification of educational platforms affects drivers' motivation to learn. The influence of individual elements of gamification on motivation was described. Moreover, the research contributes to understanding what demographic characteristics of drivers are related to the perception of different motivational factors used in gamified platforms. To advance understanding if and how educational gamification fosters and influences driver learning, the following three research questions were analyzed: (1) To what degree does educational gamification in general increase drivers’ perceived motivation in learning? (2) To what degree do specific game elements impact perceived motivation in learning? (3) Are the benefits of gamification limited to or enhanced in participants with specific demographic characteristics? The study (n = 30) examined how participation in the gamified course overall impacts drivers’ motivation, and described the impact of individual gamification elements on motivation. The study demonstrates that a large part (69,6%) of participants reported that, in general, the educational gamification environment used increased their perceived motivation. Participants found it more motivating than a traditional course. Game elements related to tracking one’s own progress were found to be most motivating. The involvement of the respondents was strongly related to the need for clearly defined goals that they should pursue when using the platform. These goals should be clearly explained, with a clear system of challenges and rewards. The study showed the benefits of gamification were not limited to participants with specific demographic characteristics. Conducted research suggests that the implementation of gamification schemes in e-learning may bring many benefits which are connected with increasing drivers’ engagement in learning and their vocational development. The results indicate a positive recipience of the proposed gamification elements and high level of their acceptance among the people who are about to enter professional driving profession.

Correlation of Work Fatigue and Mental Workload in Train Drivers: A Cross-sectional Study.

Evidence suggests that train drivers experience a high level of fatigue and mental workload. The present study aimed to assess overall, physical, and mental fatigue levels and their correlations with the mental workload in the metro train operation. Study Design: A cross-sectional study. This study was conducted on all 1194 train drivers in the Tehran Metro. The train drivers completed the Samn-Perelli Fatigue Scale and the Fatigue Assessment Scales at the beginning and end of the shift. In addition, they completed the National Aeronautics and Space Administration Task Load Index in the middle and at the end of the shift. Correlation and regression analyses were performed on the data to test the study hypothesis. Overall, physical, and mental fatigue levels increased significantly at the end of the shift compared to the onset of the shift (P<0.001). The mental workload and related dimensions were significantly increased at the end of the shift compared to the middle of the shift (P<0.001). Mental demand was the most important workload problem among the train drivers. The highest correlation was found between overall workload and time pressure (R=0.68, P<0.001). The mental workload had a significant correlation with work fatigue in the train drivers. Control measures should be focused on the mental workload and related dimensions, especially mental demand and time pressure.

Institutional dynamics and road accidents in the road haulage sector: the moderating role of information communication technology

PurposeThe purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).Design/methodology/approachThe study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.FindingsThe results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.Practical implicationsThe results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.Originality/valueThis research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

LOCATION MODERATES THE EFFECT OF COGNITIVE TRAINING ON CRASH RISK OVER 20 YEARS: AN ANALYSIS OF THE ACTIVE STUDY

Abstract Driving is a critical everyday function that helps older adults remain independent. The Advanced Cognitive Training in Vital Elderly (ACTIVE) study has shown cognitive training improves driving safety outcomes for older adults. Few studies have examined the longitudinal effects of cognitive training on crash risk beyond 5 years. To address this empirical gap, we aimed to determine the effects of cognitive training on crash risk over 20 years, and how urbanicity moderates these relationships. Using participants from the no-contact control and intervention (speed of processing, memory, and reasoning training) groups in the ACTIVE study (n=2170) and state-recorded crash reports, cox proportional hazards models were used to examine the effect of three cognitive training interventions as predictors of time to first at-fault crash over 20 years. Participants (mean age 73, 73% White, 23% Male) reported driving 90.6 miles/week on average and 12.6% experienced an at-fault crash. Overall, speed of processing training was the only intervention related to lower crash risk, but this varied by urbanicity. Namely, speed of processing training was related to lower crash risk for individuals living in rural environments (HR=.16, 95% CI [.04-.73], p=.018) but not for individuals in urban environments (HR=.89, 95% CI [.54-1.50], p=.679). Findings highlight the safety benefits of speed of processing training for older drivers living in rural environments where more fatal crashes occur. However, interventions are still needed to improve safety in urban environments where more crashes occur generally. Consideration of location in future interventions may help improve safe driving for older adults.

Optimising Traffic Safety – Locating Traffic Gendarmes Based on Multi-Criteria Decision Making

Turkey’s expanding population and growing economy have resulted in a significant increase in automobile ownership, leading to a rise in traffic volume and, subsequently, an increase in the number of accidents. The increase in the number of deaths and injuries caused by traffic accidents has motivated authorities and automobile manufacturers to work together to mitigate the impact of traffic accidents. Therefore, the demand for better roads, modern technologies and higher-quality driver training is becoming increasingly urgent for traffic safety. Due to the scale of harm to the country’s economy and society caused by the material and moral losses, resulting from traffic accidents, traffic safety and management is one of the most important government initiatives. One of the responsible units of traffic safety and management in Turkey is the traffic gendarme. This study reviewed the categories of traffic accidents, the number of accidents, and the road network that occurred in a province's gendarme responsibility area in Turkey and linked them with the number of traffic gendarmes in that province. Thus, the study utilised mixed integer programming based on multi-criteria decision-making methods to identify the areas where these traffic gendarmes will be deployed according to established principles.

Human reliability and Organizational factors—How do Human Factors contribute to Signals Passed at Danger?

The majority of railway incidents happen due to human error. Historically, human error has been split into active and latent errors, both to be investigated. Active errors are linked to a specific individual, while latent errors tend to be associated with procedures and higher levels of automation and safety barriers. Active errors are analysed with Survival Analysis, fitting several functions and the Cox Proportional Hazards model. This used a train driver database and Signal Passed at Danger (SPAD) information. A translated surveying tool is used to study latent errors and organizational factors. After translation, this tool was validated with Confirmatory Factor Analysis. Results suggest that active errors, in the form of SPADs are influenced by factors as age, experience, average length of certified itineraries and previous SPADs. The mean time between failure for a train driver in such incident is between 1000 and 1200 days. At an organizational level, Job Satisfaction is related with experience, while General and Safety Culture is related with age, position, and employer. Occupational Stress seems to be independent of the factors presented as well as the geographical location. Findings of this study identify both personal and organizational factors of the occurrence of SPADs, improving ability for better resource allocation (in the case of training or train driver allocation) or implement risk control measures (for example stricter scheduling rules).

Communication Skill Training for Female Online Ojek Drivers

Communication Skill Training for Female Online Ojek Drivers

Motorized two-wheeler riders’ rear brake application in sudden hazardous event of animal crossing

ABSTRACT This study aims to quantify the riders’ performance in the sudden event of animal crossing using explanatory variables such as psychological riding conditions and socio demographic parameters. The participants were asked to ride four sessions on the motorized two-wheeler simulator in randomized order: 1) Base, 2) Distraction, 3) Time pressure, and 4) Distraction along with Time pressure. The rear brake application was classified into four groups using K-means clustering: No braking, Mild braking, Harsh braking, and Very Harsh braking. Further, a multinomial logistic regression model was developed to quantify the rear braking behavior. The results from the study revealed that the odds of applying the harsher brakes are only 0.32 times in comparison to mild braking when riders are distracted. Overall findings indicate that riders’ psychological conditions can alter rider’s behavior, and driver training focusing on several hazards can further help in improving road safety.

Deep learning assisted three triboelectric driving operation sensors for driver training and behavior monitoring

Improving the driving skills of drivers, particularly during the training stage, is crucial in reducing the likelihood of road traffic accidents. In this work, a driver training assistance system (DTAS) is developed for driver training and behavior monitoring. The DTAS integrates three triboelectric driving operation sensors, including gear shift sensor, steering angle sensor, and pedal sensors. Through the ingenious structural design of contact-separation and freestanding-triboelectric-layer mode, these triboelectric sensors have the characteristics of simple structure, easy manufacture and installation, and self-powered, which avoids the complex wiring problem in the limited space of the vehicle. The basic electrical performance test of triboelectric sensors and driving simulation experiment show that the developed DTAS can monitor the driver behavior and provide the feedback on each driver’s operation process in real-time. Combined with deep learning (DL) technology, the DTAS can identify whether the driving operation of drivers in specific training scenarios is correct or not, with an accuracy rate of 97.5%. This work is aimed at assisting the novice or learner drivers in driving training, which helps to improve their driving skills and form good driving habits. The proposed scheme can provide new ideas for the innovative exploration of driving training modes without coaching.

Job satisfaction and perceived workload in the context of personality typology among subway train drivers

Job satisfaction is a highly relevant topic across all sectors of the national economy worldwide. A contented employee significantly enhances a company’s performance compared to a dissatisfied one. Simultaneously, a contented employee increases the human capital value of the company, which has a substantial impact on its overall value. However, employee satisfaction is not a static state; it can be influenced by various factors, one of which is perceived workload resulting from the nature of the job. The aim of this article is to investigate whether there is a demonstrable impact of perceived workload on employee satisfaction. This relationship is examined within the context of subway train drivers in the Czech Republic. In exploring this relationship, we also delve into the psychological factor of whether there is a connection between perceived workload and the satisfaction of subway train drivers based on their personality types according to the MBTI test. These dependencies are assessed through correlation analysis using a comprehensive dataset obtained. In the course of the research, data were collected from the entire basic sample of respondents, namely from 654 subway train drivers. The results confirmed the existing influence of perceived workload on employee satisfaction and, concurrently, the influence of perceived workload on employee satisfaction based on the personality typology determined by the MBTI test. These findings are undoubtedly beneficial for the management of transportation companies, particularly those involved in passenger transportation, specifically in the provision of subway services.

Train driver selection: The impact of cognitive ability on train driving performance

AbstractTrain driving is a demanding form of human performance where inattention or distraction can lead to serious errors and accidents. Train drivers, therefore, require a unique set of abilities to deal with these demands, especially when exposed to competing or conflicting performance expectations (e.g., on‐time performance and following safety rules). Cognitive abilities, in particular, are considered essential to safe and effective train driving. Selective attention is one such ability, however, other cognitive abilities can be equally important. Drawing on self‐control theory, this article examines the combined effect of selective attention, fluid intelligence, and verbal reasoning on train driving performance. The results of a study involving 101 experienced train drivers indicates that drivers with low selective attention, low fluid intelligence, and low verbal reasoning perform worse on a train simulator driving assessment than drivers who are higher in these cognitive abilities. The results from this study provide direction for future rail safety research and guidance for practitioners responsible for assessing and selecting train drivers.

The influence of train driver's foreign body penetration experience on hazard perception sensitivity: the mediating role of sustained attention

The influence of train driver's foreign body penetration experience on hazard perception sensitivity: the mediating role of sustained attention

Driving behavior assessment: A practical study and technique for detecting a driver's condition and driving style

New research confirms that driving mistakes account for almost 75 % of all traffic accidents. Recently, many researchers have studied the recognition of driving behavior, including aggressive, fatigued or drowsy driving. The principal aim of this work is to present a combination approach for evaluating driver behavior, focuses on the analysis of numerous driving-related parameters and the detection of driver fatigue and drowsiness. Experimental research is carried out using a monitoring unit which can be mounted in any vehicle fitted with CAN (Control Area Network) technology, and which monitors current driving actions. This work combines the analysis of driving parameters such as engine speed, vehicle speed, accelerator pedal position, steering wheel angle, engine noise intensity, fuel consumption and, finally, the quantity of exhaust gases generated to define whether driving is normal or aggressive. Analysis of the driver's face enables us to detect fatigue and know whether the driver is asleep on the basis of facial features. This proposed detection method achieved an average accuracy of 99.10 %. The information gathered for each driving style is recorded, in order to build up our own data and analyze it carefully. In-depth study of these parameters reveals the boundaries that define driving status and style. Experimental and simulation results confirm that the proposed system can effectively detect driving states and driver reactions, with the aim of guaranteeing a sufficient and acceptable level of safety. This study can be used to improve policies and design more robust driver training and education programs.

THE ASSOCIATION BETWEEN INDIVIDUAL, PHYSICAL, AND PSYCHOSOCIAL RISK FACTORS AND OCCUPATIONAL FATIGUE AMONG COMMUTER LINE TRAIN WORKERS

Introduction: Occupational fatigue affects workers in various industries including transportation. Commuter train drivers and office workers are subjected to high levels of physical and psychosocial stress, which can lead to occupational fatigue. Aims: to examine the relationship between individual, physical, and psychosocial risk factors and occupational fatigue in commuter train workers in Jakarta, Bogor, Tangerang, and Bekasi. Methods: Individual (i.e., age, gender, marital status, type of work, duration of work, and smoking status), psychosocial (i.e., effort, reward, overcommitment, monotonous work, social support, job satisfaction, and work stress) factors, and occupational fatigue were investigated in 78 commuter line train workers (both drivers and officers). Observing workers' activities yielded physical factors (awkward posture, repetitive work, prolonged work, and material manual handling activities). The association between each risk factor and occupational fatigue was investigated using a logistic regression model. Results: Commuter line officers (OR 4.96, 95% CI 1.77 – 13.85), those with high overcommitment (OR 3.16, 95% CI 1.25 – 8.00), and those with high work stress (OR 1.54, 95% CI 1.19 – 2.00) were more likely to report occupational fatigue than train drivers, who reported low overcommitment and low work stress, respectively. When compared to those who reported low job satisfaction, those who reported high job satisfaction were less likely to report occupational fatigue (OR 0.19, 95% CI 0.07 – 0.52). Conclusion: Job position, overcommitment, and work stress were associated with occupational fatigue.

Disabled people’s accessible taxi experiences in Toronto, Canada

Many paratransit agencies contract out trips to accessible taxi services. The literature has identified an array of transport barriers facing disabled people, and offers useful insights into how they experience different transport modes. However, remarkably little attention has been given to understanding how disabled people experience accessible taxi trips. In this paper, we present findings from a study focused on understanding how disabled people experience accessible taxi services in Toronto, Canada. Findings emerged from a thematic analysis of 590 customer complaint reports and 494 driver-reported incident reports that were provided by a local accessible taxi brokerage. To question the embodied experiences of disabled people during accessible taxi trips, we employed a critical disability studies perspective informed by phenomenological and critical ableist studies. Findings underscore the temporal experiences of disability, while highlighting ableist aspects of accessible taxi services that are contributing to various barriers for disabled riders relating to service quality issues, safety concerns, and inflexible taxi service policies. In this paper, we call for enhanced disability-related training for drivers, flexible accessible taxi policies that better account for the needs of disabled riders, improved communication protocols, and greater engagement with disabled people when developing new policies and operational changes.

From fear to forecast: The role of simulators, accompanied driving, age, gender, and information-processing style in driver training and beyond

BackgroundEven though accompanied driving and simulator training are common, clarity on their usage trends and effectiveness is lacking. This research aimed to deepen the understanding of the relationships between personal characteristics, pre-licence accompanied driving, self-reported post-licence driving behaviour, and driving performance scores during simulator lessons. MethodsWe used data from a questionnaire completed by simulator and non-simulator students (total n = 3,761). Data were analysed by dividing the sample into two groups based on variables such as gender, age at licensure, education level, fear of driving a car when starting driver education, information-processing style, participation in accompanied driving, and the number of driving simulator lessons completed. ResultsMales took fewer on-road lessons and reported lower fear, but they had poorer simulator safety scores than females. Younger learners required fewer lessons and test attempts, were less fearful, and violated traffic rules more than older respondents. Higher-educated respondents had more fear and safer driving scores in the simulator. Thinkers, who were typically more educated, showed more caution in the simulator and on the road, and were older at licensure. Compared to regular students, students participating in accompanied driving were younger at licensure. Moreover, students with a higher driving skill score in the simulator were less fearful and needed slightly fewer attempts to pass the road driving test. Discussion and conclusionThe fear towards driving, which is strongly linked to personal characteristics, provides a logical explanation for the progression of students through driver education. Furthermore, this study illustrated the possibility of considering information-processing styles, education level, and driving simulator performance in driving education. However, in order to conclusively study the safety-effectiveness of accompanied driving and simulator training, further research in the form of a randomised controlled trial is necessary.

Sustainable Technology Strategies for Transportation and Logistics Challenges: An Implementation Feasibility Study

Transportation and logistics are the basic building blocks in the socio-economic development of a country. The pandemic altered the landscape of the transportation and logistics sector where organizations had to look for new technology-based solutions. Block chain and digital trucking are emerging concepts, which were further accelerated by COVID-19, to manage the challenges in the transportation and supply chain industry. This study, therefore, investigates the challenges faced by the transportation industry during and post COVID-19 and, consequently, identifies relevant sustainable strategies to combat these challenges in a developing-economies context. Data were collected through interviews from 20 key personnel working in managerial positions in the transportation industry of Pakistan, a developing economy. The findings of this study indicate that the challenges faced by the transportation industry are reduced import–export, local market orders and revenues, supply limited to a few edible items, increase in e-commerce, new entrants in the market and operational issues, such as lack of standard operating procedures (SOPs), performance management and training of drivers. These challenges were more pronounced in the COVID-19 era; however, they are still impacting the industry. Thus, in the post-COVID-19 era, transportation companies need to opt for efficient strategies, such as contactless deliveries, expansion in e-commerce, tech-based performance management of drivers and digital trucking for sustainability, in a developing economy’s transportation and logistics sector.

Remote control concept for automated trains as a fallback system: needs and preferences of future operators

Purpose Increasing demand on rail transport speeds up the introduction of new technical systems to optimize the rail traffic and increase competitiveness. Remote control of trains is seen as a potential layer of resilience in railway operations. It allows for operating and controlling automated trains and communicating and coordinating with other stakeholders of the railway system. This paper aims to present the first results of a multi-phased simulator study on the development and optimization of remote train driving concepts from the operators’ point of view. Design/methodology/approach The presented concept was developed by benchmarking good practices. Two phases of iterative user tests were conducted to evaluate the user experience and preferences of the developed human-machine-interface concept. Basic training requirements were identified and evaluated. Findings Results indicate positive feedback on the overall system as a fallback solution. HMI elicited positive emotions regarding pleasure and dominance, but low arousal levels. Train drivers had more conservative views on the system compared to signalers and students. The training activities achieved increased awareness and understanding of the system for future operators. Inclusion of potential users in the development of future systems has the potential to improve user acceptance. The iterative user experiments were useful in obtaining some of the needs and preferences of different user groups. Originality/value Multi-phase user tests were conducted to identify and to evaluate the requirements and preferences of remote operators using a simplified HMI. Training analysis provides important aspects to consider for the training of future users.

An Integrated Method for Reducing Arrival Interval by Optimizing Train Operation and Route Setting

The arrival interval at high-speed railway stations is one of the key factors that restrict the improvement of the train following intervals. In the process of practical railway operation, sudden conflicts occur sometimes. Especially when the conflict arises at the station, because the home signal cannot be opened in time, the emergency may affect the adjustment of the train operation under the scheduled timetable, resulting in a longer train following interval or even delay. With the development of artificial intelligence and the deep integration of big data, the architecture of train operation control and dispatch integration is gradually improving from the theoretical point. Based on this and inspired by the Green Wave policy, we propose an integrated operation method that reduces the arrival interval by avoiding unnecessary stops in front of the home signal and increasing the running speed of trains through the throat area. It is a two-step optimization method combining both intelligent optimization and mathematical–theoretical analysis algorithms. In the first step, the recommended approaching speed and position are obtained by analytical calculation. In the second step, the speed profile from the current position to the position corresponding to the recommended approaching speed is optimized by intelligent optimization algorithms. Finally, the integrated method is verified through the analysis of two distinct case studies. The first case study utilizes data from the Beijing–Shanghai high-speed railway line, while the second one is based on the field test. The numerical result shows that the proposed method could save the entry running time effectively, compared with the normal strategy given by the train driver. The method can mitigate controllable conflict events occurring at the station and provides theoretical support for practical operation.