Obtaining a driver's license can significantly impact a person’s quality of life, unlocking opportunities in terms of employment and social participation. However, earning a driver’s license can be challenging, especially for individuals with ADHD. Common symptoms of ADHD include difficulties focusing, planning, organizing, and completing tasks. These challenges can hinder individuals in completing the steps essential for driver education, such as structuring training and studying for the theoretical test. Based on existing theory and interviews with driving instructors, we have developed a prototype for an app designed to aid people with ADHD during the driver’s license process. The interviews focused on challenges individuals with ADHD face throughout the process. We found that studying for the theoretical test and maintaining structure were often challenging. The app design includes features to help users plan and structure their driver’s education, as well as interactive tools for studying theory. The app is based on previous research concerning the benefits of interactive learning for individuals with attention deficits, and research on how technology can help people with ADHD create structure and achieve their goals. We plan to continue developing the app by conducting usability and validation studies. The app will be demonstrated at the conference. 

Obtaining a driver's license can significantly impact a person’s quality of life, unlocking many opportunities, particularly in terms of employment and social participation. However, earning a driver’s license can be challenging, especially for individuals with neurodevelopmental disorders (NDDs), such as ADHD and ASD. The symptoms of these can make it more difficult to obtain a driver’s license. Research on how to mitigate the difficulties faced by people with NDDs during the licensing process is scarce, and, to the best of our knowledge, no previous study has investigated this issue in a Swedish context.The Swedish driving license authorities are currently reviewing the driver education system. To ensure that future improvements to the education system effectively support people with NDDs, it is essential to understand how it can be designed to help this group overcome their challenges. Thus, the aim of our study is to contribute to this understanding by identifying the challenges this group faces when learning to drive, and how driving instructors work to mitigate these challenges when teaching. Thirteen driving instructors were interviewed about the challenges individuals with ADHD and ASD face when obtaining a driver’s license and how the instructors address these challenges. The preliminary results highlight the importance of communication, supporting learners in structuring their education, using adaptive teaching methods, and implementing continuous assessment. Our results aim to provide valuable insights that can serve as a foundation for future research and practice focused on supporting individuals with ADHD and ASD in driver education

During the development of the European Rail Traffic Management System (ERTMS), several changes and improvements have been made to the driver-machine interface (DMI). The intention is to refine the train driver support by adding, removing, or clarifying signal information. In ERTMS Baseline 3, major DMI changes have been made between onboard versions 3.4 and 3.6. This includes clarification about speed targets and a simplified color strategy for target speed monitoring. This paper presents the effects of the DMI version shift on running time, driver target braking toward a European Train Control System target, and driver workload. In an electrical multiple unit train driver simulator, 39 student train drivers tested two different DMI versions on a 16 km railway line. In addition, the drivers rated the driver task workload using the NASA Task Load Index. From the results of this study, it can be concluded that drivers, despite a longer braking phase, go faster with version 3.6 than with version 3.4. The running time difference was about 1%. Although the driving task was short, with a low workload demand, the train driver workload was clearly affected by the onboard version, such that with the later version (3.6), the workload was statistically significantly lower.

Obtaining a driver's license can greatly improve a person's life by unlocking many opportunities, particularly in terms of employment and social participation. However, for some individuals, especially those with autism spectrum disorder (ASD), earning a driver's license can be more difficult. ASD involves cognitive challenges as well as difficulties with social communication, which can, for example, lead to struggles with multitasking, making quick decisions, and understanding social cues or communicating with other drivers, skills that are essential for safe driving. These cognitive and social communication difficulties may also result in learning challenges during driver education. Research on how to address the challenges faced by people with ASD in driver education is limited, and, to the best of our knowledge, no previous study has investigated this issue in a Swedish context.The Swedish driving license authorities are currently reviewing the driver education system. To ensure that future improvements effectively support people with ASD, it is essential to understand what is needed to help this group overcome their challenges. Therefore, the aim of our study is to contribute to this understanding by identifying the challenges faced by individuals with ASD when learning to drive, and how driving instructors work to address these challenges. Thirteen driving instructors were interviewed about the difficulties individuals with ASD encounter during driver education and the strategies the instructors use to mitigate these challenges. The interviews were analyzed using content analysis. The preliminary results highlight the importance of effective communication. The driving instructors emphasize the need to adapt their communication style, focusing on aspects such as how they phrase sentences, how they listen to the learner, non-verbal cues, and their interpretation of the learner’s responses. They also highlight the importance of functional communication in the learner and how they work to encourage it. Our results aim to provide valuable insights that can serve as a foundation for future research and practices focused on supporting individuals with ASD in driver education.

Young drivers are a high-risk group for road traffic accidents, highlighting the need for advanced methods to assess and improve risk awareness. With driving simulators being considered as a possible mandatory part of the Swedish driving test, this study examines the effects of different weather conditions on performance and perceived risk during simulator-based driving tests.

26 participants (mean age = 19, SD = 2, 12 male, 11 female, and 3 unspecified) mainly recruited at an automotive high school took part in the study. All participants completed 14 driving situations in a fixed-based simulator. Weather conditions—daytime, nighttime, rain, and fog—were varied in a rolling scheme, with 3–4 traffic situations per condition. Participants, divided into four groups, experienced all weather conditions. 

Outcomes were recorded as pass/fail and supplemented with self-assessment ratings of performance and perceived risk for each situation. There was a statistically significant effect of weather conditions on driving performance, F(3, 69) = 2.973, p < .05. The test performance score (M ± SD) was highest in daytime (.64 ± .37) and nighttime (.64 ± .34) followed by rain (.58 ± .38), and fog (.43 ± .40). However, post hoc analysis with a Bonferroni adjustment indicated no statistically significant pairwise differences. There was no statistically significant effect of weather conditions on self-assessed driving performance or on perceived risk. This study offers new insights into using light and weather conditions in simulator-based driver assessment.

The driver's brake behavior has a direct effect on the deceleration of the train in terms of strength and duration, which can affect passenger comfort, and in the long run also efficiency and energy consumption. Increased knowledge of these effects may be used to improve passenger comfort, save energy, and as an important input for rising technology developments such as Connected-Driver Advisory System (C-DAS) and Automatic Train Operation (ATO). To examine the effect of various deceleration levels on passenger comfort, a field study was conducted with a Swedish EMU of Bombardier Regina X52 type in regular traffic in northern Sweden. The train driver was braking according to a 2X2 factorial study design, altering both the main deceleration (until 20 km/h) and the deceleration to stop (from 10 – 0 km/h). Deceleration to stop includes two parameters, the deceleration and jerk effect. A high-performing GPS was used to measure deceleration and passengers were asked to rate the level of comfort on a scale from 0 (only comfortable) to 100 (very uncomfortable). The hypothesis was that both decelerations respectively affect the passengers' experienced comfort.  In total, there were 23 stops, and 91 passengers took part, rating various numbers of stops according to their traveled distance. According to the 2X2 design, the train driver altered the brake level.  The measured average levels were -0,76 m/s2 (high) and -0,46 m/s2 (low) for main deceleration. For deceleration to stop the average levels were -0,55 m/s2 (high) and -0,37 m/s2 (low).  A 2X2 between-subject factorial ANOVA with ETA- square as effect size was carried out using SPSS. This revealed a significant main effect of main deceleration, such that higher deceleration force led to higher ratings of discomfort, M= 23.79 (SD = 19.63) compared to M = 9.38 (SD = 13.00), F (1, 652) = 116.20, p < .01, 

η2p𝜂p2 = .151. There was also a significant main effect of the deceleration to stop, such that higher deceleration force led to higher ratings of discomfort (M = 17.81 (SD = 18.25) compared to M = 13.79 (SD = 17.22), F (1, 652) = 5.99, p = .015, 

η2p𝜂p2 = .009. There was no interaction effect.  From this study, and a somewhat unexpected, it can be concluded that the experienced comfort at all these various levels of deceleration was generally high. Further, both the main deceleration and the deceleration to stop, respectively, affect the passenger comfort. These results can be used as input for train-driver training and railway technology developments such as C-DAS and ATO. 

The Swedish driver education curriculum is based on Goals for Driver Education GDE [1], where an emphasis on motivational factors and risk-awareness in driving is added to the traditional vehicular handling and mastering of traffic situations. A large proportion of deaths from traffic crashes are due to human causes [2] and young drivers are especially prone to crashes due to their lack of experience, lack of risk-perception, and tending to overestimate their driving ability [3]. A driver education curriculum should make sure that risk-awareness and motivational factors are trained and assessed. A challenge in driver assessment is to ensure that a driver’s risk-awareness is sufficiently tested during the on-road exam, since many risks are uncommon. Driving simulators offer a safe and controllable environment for education and training [4], and have been shown useful in systematically testing a driver's perception, risk-awareness, and performance in uncommon but safety-critical situations [5]. The potential benefit of a more unified use of driving simulators in driver education is examined in a Ph.D. project. One part of the project is an on-going study with the aim of exploring situations that are suitable for training and testing risk-awareness. The research questions are: 1) What kind of situations are suitable to include? 2) In a specific situation, which parts of GDE are covered? A web-based questionnaire will be distributed to 60 driver educators, well familiar with GDE, who will assess each situation presented both visually and verbally. Preliminary results from a pilot test with 10 participants indicate that the situations are suitable for educating and testing and that they are mainly focused on the second level of the GDE. Final results will be presented at the conference.

Young people represent a high-risk group of drivers and the prevalence of road traffic crashes among young drivers is high. Thus, to increase traffic safety, it is essential to ensure that new drivers are both sufficiently educated in and assessed for risk awareness.The aim of this study was to examine the possibility and potential benefit of using a driving simulator screening test as a complement to the existing on-road driving test. The main idea is to detect drivers who are not ready to proceed to the driving test.A comparative study was performed with participants who passed and failed a simulator test and an on-road driving test, respectively. A comparison between subjective and objective measures of performance and risk was also included. A driving simulator was placed at a traffic school and customers were recruited as participants. In total, 70 participants took part in the study and the simulated drive consisted of rural roads, urban traffic, and motorways with 16 different scenarios, constructed from the second level of the GDE matrix, to examine driving behavior, attention, and risk perception.The results show that with a screening test in a driving simulator, it is possible to detect drivers who consider themselves ready to take a driving test, but who have not yet reached the level of risk awareness required to be a safe driver. Test scenarios should be suited to detect deficiencies in risk awareness, test different levels of the GDE matrix and, to complement the driving test, be difficult to assess in an on-road driving test. Deficiencies in self-evaluation that are well-known among young drivers are again confirmed. To practice self-evaluation, the driving simulator is suggested as a pedagogical tool, linked to the GDE matrix.

In the signal planning process, the ERTMS speed profiles based on track nature needs to be complemented with additional constraints. The base profile resolving the allowed track speed, often includes several speed changes which can be difficult for the train driver to follow. One approach to deal with this problem is to filter the base profile, reducing the number of changes and giving the driver more time for attention.This paper presents the effects of a speed profile filtering principle, based on possible time usage during a speed increase, on train energy consumption, train driver braking behavior, running time, and driver workload. In an Electrical Multiple Unit train driver simulator, 40 drivers tested three different speed profiles of a 19 km railway line. It can be concluded that differences in running time are small, that these small time-gains implies a high energy con-sumption cost, and that drivers tend to drive close to the indication braking curve in the beginning of the braking phase. Further, the drivers rated the driver task workload low for all filter conditions. Accordingly, a certain filter level is required to get capacity and energy effects.