Driving Instructors’ Experiences with the Goals for Driver Education Matrix: Challenges, Usability, and Opportunities for ImprovementKjellander, D., Herzberg, L. Thorslund, B.

The Swedish driving license syllabus is based on the Goals for Driver Education (GDE) matrix, which outlines the skills and knowledge required to become a safe driver. While essential for ensuring high-quality training nationwide, many traffic instructors find the GDE matrix complex and difficult to explain. This apparent contradiction may be attributed to the fact that the GDE matrix was not originally designed as a practical tool for driving instruction, but rather as a tool for analysis. However, with suitable clarifications and adjustments, it has the potential to serve as a valuable resource for both instructors and learner drivers.

The purpose of this study was to explore driving instructors’ experiences of the GDE matrix and to examine why it may be difficult to understand and put to practice. The study also aimed to suggest improvements to increase its usability. The study was conducted in several steps.

First, driving instructors were invited to participate in a questionnaire study, which was completed by 68 active instructors. The questions assessed both their knowledge and perceived usefulness of the GDE matrix. Next, interviews with driving instructors are planned, in which participants will be asked to describe the GDE matrix. These interviews will be recorded and analysed to identify connections between the theoretical model and its practical application in driver education. Alternative explanatory texts will then be developed and compared to the original texts in tests involving a new group of driving instructors. This final step aims to evaluate whether the findings of the study may help make the GDE matrix more useful and effective.

Results from the questionnaire revealed that respondents were generally familiar with the content and concept of the GDE matrix but were not confident in explaining it to others. Moreover, the perceived usefulness of the matrix was rated as moderate. Results from the planned interviews and text-testing phase will also be presented at the conference.

Young drivers' elevated crash risk is linked to inexperience, low risk awareness, and underdeveloped cognitive control. To improve driving testing, several countries use hazard perception tests, and Sweden is piloting a simulator-based screening test as a potential complement to the on-road driving test. These screening tests would have to be developed in several versions and would have to be randomized. The aim of this study was to examine whether introducing controlled visual variations into traffic situations would alter the overall difficulty structure of the simulator-based screening test, that is, whether the relative difficulty of the situations remained stable across different test versions. An experimental between-group design was used, with 127 Swedish automotive high school students randomly assigned to one of three versions of a simulator-based screening test. All versions included the same 14 traffic situations across urban, rural, and highway environments, but differed in minor design features. The screening test evaluated participants' performance in each situation (pass/fail) and the outcome from the three versions was analyzed with a Rasch analysis. The findings suggest that small variations did not compromise overall test consistency, although added pedestrians and roadside objects increased difficulty in some traffic situations. These insights support the development of fair and reliable simulator-based screening test, with potential benefits for driver testing and traffic safety.

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

Background

Traffic accidents are a leading cause of death among young people, partly due to underdeveloped executive functions like planning and impulse control. Young drivers often underestimate risks and overestimate their abilities, highlighting the need for more accurate driving tests. One solution is to use driving simulators alongside Sweden's current on-road and theoretical exams. While simulator tests show promise, further development is needed. A screening test has been created to identify risky drivers, using challenging situations to assess hazard perception and risk awareness. To make it viable, multiple versions of these scenarios must be developed and validated.

Aim

This study aimed to assess how small variations in the simulator screening test affect the results. This knowledge is essential for creating numerous unpredictable, fair, and reliable variations of the screening test. The following research questions were formulated:

• How do small changes in the road environment or traffic impact test outcomes
• To what degree do the different test versions maintain consistent difficulty levels?

Method

A between-group design was used, with participants divided into three groups, each completing one of three versions of the same simulator test. All three versions included the same 14 situations, with small variations in the road environment or surrounding traffic. The independent variable was the version (1-3) and the situations (S1-S14), while the dependent variable was participants' overall performance and performance on individual situations (pass/ fail).

Participants

Data were collected at five automotive high schools, recruiting 126 students—92 men and 14 women. All participants were 17 years old and had extensive prior experience with the simulator used (Figure 1).

Equipment

A fixed-base high-fidelity driving simulator with Skillster software was used (skillster.se). Three tests versions were administered, each containing 14 challenging and potentially dangerous situations, set in urban traffic, on country roads, and highways. For instance, one scenario tested merging onto a highway, another handling a left turn on a country road with oncoming traffic, and a third avoiding a hidden pedestrian. The 14 scenarios had slight variations across the versions, such as different colored cars and houses or buses replaced by trucks (Figure 2). The goal was to introduce small changes between version1 and 2, and slightly more changes in version 3. In one situation, version 3 was made even more complex to test the extent of possible variations.

Procedure

Before starting the simulator test, participants were informed of their anonymity and right to withdraw. After giving consent, they were randomly assigned to one of three versions, each taking approximately24 minutes. Each situation had specific evaluation criteria, such as giving way, driving at a safe speed, and maintaining distance from other vehicles. To pass the entire test, participants had to pass all 14situations. Participants were not informed of their results.

Analysis

Data was compiled in Excel, with separate files for each version, and then analyzed in Jamovi. Rasch analysis was used to assess the difficulty of the 14 situations across the three versions, producing three corresponding result tables (Table 1-3). Situation difficulty was evaluated using the Measure parameter from the Rasch analysis, where higher values indicate more difficult situations and lower values indicate easier ones.

Results

Results show similarities between situations across versions. For instance, situation 13 was the most difficult in all versions, though slightly more so in version 3. Situation 11 was consistently the easiest. The pass rate for each situation was also similar across versions. However, some variations in difficulty warrant further examination. For example, the difficulty of situation 8 increased from version 1 to 2, and more so from version 2 to 3. Situations 3 and 9 were more difficult in version 3 than in the others.

Conclusion

Small variations in simulator test situations do not significantly affect the outcome. However, adding more changes and increasing complexity can alter the difficulty level. These insights are crucial for creating multiple unpredictable simulator screening tests with consistent difficulty. Further analysis will be conducted, and additional results will be presented at the conference.

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.