Driver Training Research Articles

Facilitate Driving with Geographical Proximity

Abstract: This research paper describes the development of a website based on remote computing with the aim of improving the connection between driving schools and automobile students. The primary purpose of this web application is to provide administrators, parents, and students with actual vehicle information, including clutch usage, speed, braking patterns, and vehicle location. This is achieved through the integration of remote data processing installed in the vehicle and sending the relevant data to web applications. This article discusses the importance of these systems in improving driver training and safety by allowing participants to remotely monitor vehicle operation, driving behavior and actions. We completed the literature review to examine existing telematics systems and their applications in the automotive industry. The work includes the selection and installation of remote data processing equipment, the development of user- friendly web interfaces using modern programming languages and methods, and scrupulous compliance with technical procedures. The main features of the web application include real-time data tracking, GPS tracking, important event alerts and notifications, and reporting and analysis capability. The implementation process is quite detailed, including hardware integration, front-end and back-end development, data storage and security measures.

The Influence of EMU Driver Education and Training on Train Driver Competency Indonesian High Speed Rail “Whoosh”

The Jakarta Bandung High Speed Train is a mass transportation that is a long-term permanent solution that is expected to overcome road traffic congestion on urban roads and roads to Bandung, two areas that are projected in the future to become megapolitan areas, roads in the surrounding area, reduce carbon emissions and air pollution, as well as effective steps to shift private vehicle users to mass transportation effectively (Ministry of Transportation, 2022). In order to increase the competence of the crew of fast train railway facilities, PT Kereta Cepat Indonesia China (PT.KCIC) in collaboration with the Indonesian Railway Polytechnic in Madiun organized EMU Driver education and training. The following is the number of EMU Driver education and training participants who do not yet have a certificate of competence for the crew of fast train railway facilities. While the questionnaire results on the Railway Suggestion crew competency variable are also dominated by answers agreeing or with an average of 82.99%. With these results it can be interpreted that after attending EMU Driver education and training affects the Competence of the Railway Facilities Crew where the results of the regression analysis obtained Y21.323 + 0.412. The intercept value is 21,323 which means that without the X variable, the competence of the crew of the railway facilities remains the value, namely 21,323. The t test data has a t count of 5.821 while the t table at the 5% level for 32 respondents is 2.014. Because t count t table then Ho is rejected and Ha is accepted. with a significance value of 0.000 (0.0000.05) This can be interpreted that EMU Driver education and training has a positive and significant effect on the competence of the crew of railway facilities.

Generation of nighttime pedestrian fatal precrash scenarios at junctions in Tamil Nadu, India, using cluster correspondence analysis

Objective Modern transportation amenities and lifestyles have changed people’s behavioral patterns while using the road, specifically at nighttime. Pedestrian and driver maneuver behaviors change based on their exposure to the environment. Pedestrians are more vulnerable to fatal injuries at junctions due to increased conflict points with vehicles. Generation of precrash scenarios allows drivers and pedestrians to understand errors on the road during driver maneuvering and pedestrian walking/crossing. This study aims to generate precrash scenarios using comprehensive nighttime fatal pedestrian crashes at junctions in Tamil Nadu, India. Methods Though numerous studies were available on identifying pedestrian crash patterns, only some focused on identifying crash patterns at junctions at night. We used cluster correspondence analysis (CCA) to address this research gap to identify the patterns in nighttime pedestrian fatal crashes at junctions. Further, high-risk precrash scenarios were generated based on the positive residual means available in each cluster. This study used crash data from the Road Accident Database Management System of Tamil Nadu State in India from 2009 to 2018. Characteristics of pedestrians, drivers, vehicles, crashes, light, and roads were input to the CCA to find optimal clusters using the average silhouette width, Calinski-Harabasz measure, and objective values. Results CCA found 4 clusters with 2 dimensions as optimal clusters, with an objective value of 3.3618 and a valence criteria ratio of 80.03%. Results from the analysis distinctly clustered the pedestrian precrash behaviors: Clusters 1 and 2 on pedestrian walking behaviors and clusters 3 and 4 on crossing behaviors. Moreover, a hidden pattern was observed in cluster 4, such as transgender drivers involved in fatal pedestrian crashes at junctions at night. Conclusion The generated precrash scenarios may be used to train drivers (novice and inexperienced for nighttime driving), test scenario creation for developing advanced driver/rider assistance systems, hypothesis creation for researchers, and planning of effective strategic interventions for engineers and policymakers to change pedestrian and driver behaviors toward sustainable safety on Indian roads.

Reconsidering screening thresholds in health assessments for obstructive sleep apnea using operational and safety incident data

The rail industry in Australia screens workers for probable obstructive sleep apnea (OSA) due to known safety risks. However, existing criteria to trigger screening only identify a small proportion of workers with OSA. The current study sought to examine the relationship between OSA risk and rail incidents in real-world data from Australian train drivers, and conducted a proof of concept analysis to determine whether more conservative screening criteria are justified. Health assessment (2016–2018) and subsequent rail incident data (2016–2020) were collected from two passenger rail service providers. Predictors included OSA status (confirmed no OSA with a sleep study, controlled OSA, unknown OSA [no recorded sleep assessment data] and confirmed OSA with no indication of treatment); OSA risk according to the current Standard, and OSA risk according to more conservative clinical markers (BMI threshold and cardiometabolic burden). Coded rail safety incidents involving the train driver were included. Data were analysed using zero-inflated negative binomial models to account for over-dispersion with high 0 counts, and rail safety incidents are reported using Incidence Risk Ratios (IRRs). A total of 751 train drivers, typically middle-aged, overweight to obese and mostly men, were included in analyses. There were 43 (5.7%) drivers with confirmed OSA, 62 (8.2%) with controlled OSA, 13 (1.7%) with confirmed no OSA and 633 (84.4%) drivers with unknown OSA. Of the 633 train drivers with unknown OSA status, 21 (3.3%) met ‘at risk’ criteria for OSA according to the Standard, and incidents were 61% greater (IRR: 1.61, 95% Confidence Interval (CI) 1.02–2.56) in the years following their health assessment compared to drivers who did not meet ‘at risk’ criteria. A more conservative OSA risk status using lower BMI threshold and cardiometabolic burden identified an additional 30 ‘at risk’ train drivers who had 46% greater incidents compared to drivers who did not meet risk criteria (IRR (95% CI) 1.46 (1.00–2.13)). Our more conservative OSA risk criteria identified more workers, with greater prospective incidents. These findings suggest that existing validated tools could be considered in future iterations of the Standard in order to more sensitively screen for OSA.

Predictive effects of organizational justice on job satisfaction in bus drivers: the moderating effects of role overload and proactive personality

BackgroundThere have been few longitudinal studies on Chinese bus drivers and the individual differences in the relationships between organizational justice and job satisfaction. This study examined the organizational justice and job satisfaction in bus drivers and the individual differences in this relationship.MethodsA two-wave longitudinal study design was employed. A first survey was conducted on 513 Chinese bus drivers in October 2021 that collected socio-demographic information and asked about their perceptions of organizational fairness. A second survey was conducted six months later that asked about role overload and job satisfaction and assessed their proactive personality type. An effect model was then used to explore the moderating effects of role overload and proactive personality type on the relationships between organizational justice and job satisfaction.ResultsBoth procedural and interactive justice predicted the bus drivers’ job satisfaction. Proactive personalities and role overload were found to enhance this relationship.ConclusionsOrganizations could benefit from screening at the recruitment stage for drivers with highly proactive personalities. Relevant training for drivers with low proactive personalities could partially improve employee job satisfaction. When viewed from a Chinese collectivist cultural frame, role overload could reflect trust and a sense of belonging, which could enhance job satisfaction. Finally, to improve employee job satisfaction, organizations need to ensure procedural and interactive justice.

Teaching advanced technology (ADAS) and use of touch screens in driver training in Norway

As many as 4,601 people were injured or killed on the roads in Norway in 2022. This number is too high and highlights the necessity of putting road safety on the agenda. The car industry today is represented by a vast increase in advanced technology for drivers to interact with, and knowing how and when to use this technology is crucial for safe driving. Thus, our research question was: Does the Norwegian driver training industry teach advanced driver assistance technology (ADAS) and touch screens in their driver training?A survey was distributed to 1,058 driving schools in Norway, resulting in 333 responses. The results showed that driving instructors spend considerably more effort on teaching inbuilt driving assist technologies that enhance driving safety than on those that are designed to enhance safety but that, if not understood well, could lead to hazardous outcomes. Suggestions on how to improve driver training and driving instructor education are made. Research and practical implications are presented to make sure that driving education is updated and aligned with technological advancements in the automobile industry and to ensure traffic safety for all road users.

How are sociodemographic differences contributing to red light violation behavior? the underlying role of gender, age, driving experience, and income

ABSTRACT This paper presents the results of the first driver behavior questionnaire (DBQ) study on analyzing Indian drivers’ aberrant behavior for red light violations (RLVs) at signalized junctions. An ordered probit model is developed using the drivers’ socio-demographic variables. The model results indicate that age has the strongest influence on drivers’ RLV behavior, followed by driving experience and level of education. The level of perceived RLV appears to increase with higher driving frequency and two-wheeler ownership. This research is also the first to analyze the aberrant behavior differences among male and female drivers concerning their demographics and driving experiences. It is unique to note that at a certain combination of various demographics (e.g., driving experience, education level, and daily trip frequency), the men and women are becoming equal in their aberrant behavior while committing RLVs. This finding is an interesting input for developing driver training and education programs.

Analysis of drivers’ take-over ability improvement and behavioral steady state in human–machine codriving vehicles

During human–machine codriving, drivers need to take over the vehicle when a take-over request (TOR) appears. If drivers have not received relevant training before driving, they may be unable to complete the take-over within the limited time, or the stability of subsequent vehicle control may be insufficient, which can lead to accidents. In this study, two types of take-over ability improvement methods are proposed. Participants were recruited and randomly divided into a control group (n = 15, no take-over training) and two experimental groups (n = 15, text-based training; n = 15, behavioral spectrum-based training). One-way ANOVA or the Kruskal–Wallis test and post hoc contrasts were used to analyze the differences in data indicators between the three groups of drivers after 20 take-over operations, and another method was proposed to validate the efficiency of the take-over operations on the stability of take-over ability. The results show that compared with the control group, both experimental groups demonstrated a significant improvement in take-over ability, with the behavioral spectrum-based training group exhibiting better take-over performance than the text-based training group. Moreover, after 14 take-over operations, drivers’ take-over ability in the behavioral spectrum-based training group stabilized. The findings of this study can contribute to the safety of human–machine codriving vehicles and the design of future driver training systems.

휠체어 이용 장애인의 저상버스 이용 실태 및 경험에 관한 연구: 인천광역시를 중심으로

This study aims to provide policy implications based on the actual usage of low-floor buses operating in Incheon Metropolitan City and the experiences of people with disabilities who use them. For the purpose of this study, a combination of quantitative research using frequency analysis based on monitoring sites and qualitative research revealing the experiences of the researcher was conducted. For this purpose, four people with severe disabilities who use wheelchairs were recruited, and the objectivity of the research was ensured through training for the recruited people with disabilities. The results of the study were derived through frequency analysis and thematic analysis of the surveyed sites, and the results were as follows: first, 80.4% of the low-floor buses were accessible, but 19.6% were not. Second, 77.5% of the bus stops were accessible. Third, 24.5% of the platform lifts (ramps) were not operational for low-floor buses. Fourth, regarding the friendliness of low-floor bus drivers, 28.2% were found to be unfriendly. Fifth, the survey revealed various inconveniences related to the place of alighting. The results of this study led to policy recommendations on the need to eradicate discrimination, introduce universal design for low-floor buses, distribute low-floor bus manuals and driver training, and expand the number of low-floor buses in order to improve the mobility rights of people with disabilities using wheelchairs.

The Effect of Job Stress on the Socio-Psychological Health of Train Drivers: The Mediating and Moderating Effects of Self-Efficacy

The Effect of Job Stress on the Socio-Psychological Health of Train Drivers: The Mediating and Moderating Effects of Self-Efficacy

Perception of drivers toward road safety and factors that cause road accidents in Riyadh city of Saudi Arabia

Injury as a result of road traffic accidents (RTA) is one of the leading causes of death and disability-adjusted life years. Strategies to handle this major public health problem, which has significant consequences for the Saudi economy and families, have been underway for many years but with very little success. This study’s main aim is to determine respondents’ perceptions of traffic safety and the factors that lead to road traffic accidents. It is a cross-sectional study conducted on randomly selected university students, faculty drivers, and visitors using King Saud University’s parking facility. Data were collected from 381 drivers using a pretested questionnaire, which comprises questions intended to attain the study’s objectives. The critical factors affecting traffic safety are public information followed by road maintenance, Garage, vehicle inspection, Road design and equipment, Training of drivers, Sanctions and Police enforcement, Protective devices and vehicle design, and post-accidental care. Road traffic accidents were found to be 39.0% with respondents aged less than 20 years, followed by ages between 20–35 years, which was 34.8%, and only 2.4% above 50 years. The most frequent occurrence of road traffic accidents was angle collision (39.0%) and back collision (18.9%), followed by hitting a fixed object (17.7%). Distraction habits during driving include cell phone usage (56.7%), followed by smoking (24.4%), and eating and drinking (18.9%) while driving. The most common traffic violations were increased speed limit (48.1) and loss of driving license (11.8%). The most common injuries were head (39.0%) and limbs (22.0%). A significant association between drivers’ age during the accident and distraction habits has been found (p < 0.000). The study demonstrated that drinking/eating, cell phone use, and violation of traffic rules are significant reasons for RTA. The findings of this study will contribute to a more comprehensive knowledge of road traffic accidents for the formation of effective strategies and evidence-based policies for the prevention of accidents.

Climate neutrality in European heavy-duty road transport: How to decarbonise trucks and buses in less than 30 years?

The decarbonisation of heavy-duty road transport is subject to many uncertainties regarding fuel choices and the role of efficiency and demand-side measures. Moreover, the various segments of heavy-duty road transport exhibit distinctive characteristics, posing challenges in identifying a one-size-fits-all solution. In a scenario-based analysis with coupled modelling of the European energy system and its endogenous transport demand (driver training, improved logistics and collective mobility) we study the decarbonisation of European heavy-duty road transport through 2050, with a granular representation of its segments in the modelling exercise. Our modelling results show that battery electric vehicles are the key enablers of climate neutrality, representing 60 %–89 % of trucks and 79 %–96 % of buses by 2050. Yet, this important level of electrification, in a climate-neutral Europe, represent at most 4 % (320 TWh) of final electricity consumption. While shifting to electric and hydrogen vehicles brings significant fuel savings (41 %–66 %) and emission reductions (33 %–60 % cumulatively), demand-side operational measures can quickly and cost-effectively complement fuel switching, bringing up to 50 % of cumulative emission savings. The modelling results are highly sensitive to policy assumptions, especially regarding those related to the role of clean hydrogen. This calls for long-term planning with stable and clear signalling of technology choices.

Influence of emotions on the aggressive driving behavior of online ­car-hailing drivers based on association rule mining

Emotion is an important factor that can lead to the occurrence of aggressive driving. This paper proposes an association rule mining-based method for analysing contributing factors associated with aggressive driving behaviour among online car-hailing drivers. We collected drivers’ emotion data in real time in a natural driving setting. The findings show that 29 of the top 50 association rules for aggressive driving are related to emotions, revealing a strong relationship between driver emotions and aggressive driving behaviour. The emotions of anger, surprised, happy and disgusted are frequently associated with aggressive driving behaviour. Negative emotions combined with other factors (for example, driving at high speeds and high acceleration rates and with no passengers in the vehicle) are more likely to lead to aggressive driving behaviour than negative emotions alone. The results of this study provide practical implications for the supervision and training of car-hailing drivers.

Are train horns improving road safety? Road users’ perspective

Train horns are used as a control at railway level crossing for safety. Despite their wide use, limited information exists on their actual safety benefits. This study used focus groups with road users to understand their perceptions of the usefulness of train horns. This study showed that the message heard by road users is very simple and contrasts with the amount of information train drivers want to convey. The perceived benefits of the train horn were: (i) an additional layer of protection at active crossings; (ii) an important safety feature at rural/passive crossings; (iii) an increased safety benefit for vulnerable road users; and (iv) a greater safety benefit at night. The disadvantages of the use of train horns were perceived as outweighed by the safety benefits. This study highlights that reducing train horns, if safe to do so, could face resistance from road users and the rail industry.

A method to enhance drivers' hazard perception at night based on “knowledge-attitude-practice” theory

During nighttime driving, the inherent challenges of low-illuminance conditions often lead to an increased crash rate and higher fatalities by impairing drivers' ability to recognize imminent hazards. While the severity of this issue is widely recognized, a significant research void exists with regard to strategies to enhance hazard perception under such circumstances. To address this lacuna, our study examined the potential of an intervention grounded in the knowledge-attitude-practice (KAP) framework to bolster nighttime hazard detection among drivers. We engaged a cohort of sixty drivers split randomly into an intervention group (undergoing specialized training) and a control group and employed a holistic assessment that combined eye movement analytics, physiological response monitoring, and driving performance evaluations during simulated scenarios pre- and post-intervention. The data showed that the KAP-centric intervention honed drivers' visual search techniques during nighttime driving, allowing them to confront potential threats with reduced physiological tension and ensuring more adept vehicle handling. These compelling findings support the integration of this methodology in driver training curricula and present an innovative strategy to enhance road safety during nighttime journeys.

Automated Detection of Train Drivers’ Head Movements: A Proof-of-Concept Study

With increasing automation in the rail sector, the train driver’s task changes from full control to a supervisory position. This bears the risk of monotony and subsequent changes in visual attention, possibly for the worse. Similar to concepts in car driving, one solution for this could be driver state monitoring with triggered interventions in case of declining task attention. Previous research on train drivers’ visual attention has used eye tracking. In contrast, head tracking is easier to realize within the train driver cabin. This study set out to test whether head tracking is a feasible alternative to eye tracking and can provide similar findings. Based on previous eye-tracking research, we compared differences in head movements in automated vs. manual driving, and for different levels of driving speed and driving experience. We conducted a study with 25 active train drivers in a high-fidelity train simulator. Statistical analyses revealed no significant difference in the vertical head movements between automation levels. There was a significant difference in the horizontal head movements, with train drivers looking more to the right for manual driving. We found no significant influence of driving speed and experience on head movements. Safety implications and the feasibility of head tracking as an alternative to eye tracking are discussed.

Automated train driving: risk analysis validation

Aim. The paper is dedicated to describing the validation of risk analysis as part of an automated train control research project. Methods. Validation was performed using several different methods. The obtained results were compared with those obtained from other sources. Additionally, an independent risk analysis was performed using the alternative MEM (minimum endogenous mortality) method. Results. The validation showed that the project’s findings are reliable. Safety Integrity Levels (SIL) 1 or 2 were confirmed for train driver substitution systems. Conclusions. It was shown that various methods should be used for the purpose of risk analysis validation. It must be taken into account that comparable, but not identical results will be obtained.

Assessing Training Methods for Advanced Driver Assistance Systems and Autonomous Vehicle Functions: Impact on User Mental Models and Performance

Understanding the complexities of Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicle (AV) technologies is critical for road safety, especially concerning their adoption by drivers. Effective training is a crucial element in ensuring the safe and competent operation of these technologies. This study emphasises the critical role of training methodologies in shaping drivers’ mental models, defined as an individual’s cognitive frameworks for understanding and interacting with ADAS and AV systems. Their mental models substantially influence their interactions with those technologies. A comparative analysis of text-based and video-based training methods has been conducted to assess their influence on participants’ performance and the development of their mental models of ADAS and AV functionalities. Performance is evaluated in terms of the accuracy and reaction time of the participants as they interacted with ADAS and AV functions in a driving simulation. The findings reveal that video-based training yielded better performance outcomes, more accurate mental models, and a deeper understanding of ADAS functionalities among participants. These findings are crucial for policy makers, automotive manufacturers, and educational institutions involved in driver training. They underscore the necessity of developing tailored training programs to facilitate the proficient and safe operation of increasingly complex automotive technologies.

Examining Patterns and Predictors of ADHD Teens' Skill-Learning Trajectories During Enhanced FOrward Concentration and Attention Learning (FOCAL+) Training.

Examine patterns and predictors of skill learning during multisession Enhanced FOrward Concentration and Attention Learning (FOCAL+) training. FOCAL+ teaches teens to reduce the duration of off-road glances using real-time error learning. In a randomized controlled trial, teens with ADHD received five sessions of FOCAL+ training and demonstrated significant reductions in extended glances (>2-s) away from the roadway (i.e., long-glances) and a 40% reduced risk of a crash/near-crash event. Teens' improvement in limiting long-glances as assessed after each FOCAL+ training session has not been examined. Licensed teen (ages 16-19) drivers with ADHD (n = 152) were randomly assigned to five sessions of either FOCAL+ or modified standard driver training. Teens completed driving simulation assessments at baseline, after each training session, and 1 month and 6 months posttraining. Naturalistic driving was monitored for one year. FOCAL+ training produced a 53% maximal reduction in long-glances during postsession simulated driving. The number of sessions needed to achieve maximum performance varied across participants. However, after five FOCAL+ training sessions, number of long-glances was comparable irrespective of when teens achieved their maximum performance. The magnitude of reduction in long-glances predicted levels of long-glances during simulated driving at 1 month and 6 months posttraining but not naturalistic driving outcomes. FOCAL+ training provided the most benefit during training to teens who were younger and had less driving experience. FOCAL+ training significantly reduces long-glances beginning at the 1st training session. Providing five FOCAL+ training sessions early on during teen driving may maximize benefit.

Influence of commercial drivers’ risky behavior on accident involvement: moderating effect of positive driving behavior

The influence of risky driving behavior on road traffic accidents (RTAs) is a relationship that requires draconian measures to curtail the rising surge of road traffic accidents among commercial drivers. Any attempt to ignore this will result in continuous loss of lives and properties, thus weakening the global economy, especially in developing countries. The risky driving behaviors of commercial drivers (truck and taxi drivers) in Nigeria require a panacea due to their contribution to RTAs. The study examines the moderating effect of positive driving behavior on commercial truck and taxi drivers’ risky driving behavior and accident involvement relationship. A total of 1823 commercial vehicle drivers (943 taxi drivers and 880 truck drivers) completed the driver behavior questionnaire (DBQ), while the structural equation modeling (SEM) method was used for the analysis. The results indicated a significant moderating effect of positive driving behavior on the risky driving behavior and accident involvement relationship for both commercial truck and taxi drivers in Nigeria. Specifically, the truck drivers had a positive moderating effect, resulting in a decrease in RTAs with an increase in positive driving behavior. In contrast, the taxi drivers had a negative moderating effect. The results suggest that increasing positive driving behavior among truck drivers will enhance their safety, while taxi drivers will need more assessment to identify other risky behaviors that could expose them to more RTAs despite the positive driving behavior. This study will aid decision makers, transport trainers, and driver employers in knowing the importance of enforcing and promoting positive driving behaviors among drivers and include it in driving policy and driver training curricula towards RTA reduction.