Year to year, vehicles are becoming more advanced, and manufacturers offer newer support systems. Progressive tech-nology development must be followed by relevant sociological changes, including establishing a proper user aware-ness level. Even though compulsory driver training, required before obtaining a license, consists of selected support features, e.g. ABS (Anti-lock Braking System), it does not provide novice drivers with the necessary practical skills and knowledge of all automation features available on the market. To reduce the human error factor, the European Parlia-ment adopted new regulations, including minimum safety requirements for new vehicles. This paper identifies the gap between the current approach toward teaching automation and necessary changes that should be made to ensure road safety. It provides an overview of ADAS functions allowed to be used during driving license exam of category B in different European countries.Moreover, the publication contains results of work carried out under the Trustonomy project. Outcomes obtained from the questionnaires were used to develop new driver training curricula. The publication discusses the developments of a survey conducted among 83 Polish drivers and 91 car fleet managers. The paper reveals their attitude and expectations towards driver training. The results indicate that despite the awareness of ADASs positive impact on safety (80% of drivers vote, 96% of car fleet managers votes), many people still didnt take part in any training and still do not know how to use systems properly. Even more worrying is the fact that more than 50% of drivers admitted they acquired knowledge about system operation based on their own mistakes. Many responders expressed their interest in acquiring new knowledge. This situation indicates an urgent need to introduce changes to the driver training system. Therefore, the publication highlights different regulatory boundaries across Europe and stresses the need to update existing curricula to introduce proper automation-related training.

In highly automated vehicles the driver benefits from the technology which is able to control movement of the vehicle with only his or her supervision. It rises questions on how to manage driver attention in the face of sudden events that need his intervention. The following paper focuses on the result of the study of different Human–Machine Interfaces for Highway Chauffeur—SAE J3016 level 4 system capable to automatically drive in highway conditions—and the performance of control transition to the human driver in situation of operational domain exceedance. The study performed in high-fidelity car simulator for 81 participants that uses different HMI’s: visual, auditory, haptic and personalized auditory shows the directions in which the novel interfaces may be developed to better interact with the users in safety–critical situations. Tactile-haptic interface gave the best prospects both in terms of objective indicators like time of reaction, and workload and in subjective users’ opinions.

In L3–L4 vehicles, driving task is performed primarily by automated driving system (ADS). Automation mode permits to engage in non-driving-related tasks; however, it necessitates continuous vigilance and attention. Although the driver may be distracted, a request to intervene may suddenly occur, requiring immediate and appropriate response to driving conditions. To increase safety, automated vehicles should be equipped with a Driver Intervention Performance Assessment module (DIPA), ensuring that the driver is able to take the control of the vehicle and maintain it safely. Otherwise, ADS should regain control from the driver and perform a minimal risk manoeuvre. The paper explains the essence of DIPA, indicates possible measures, and describes a concept of DIPA framework being developed in the project.

Understanding the information conveyed by symbols is extremely important from the point of view of road safety. The symbols used on road signs and integrated into the vehicle must be clear and legible. This is especially important given the lack of regulations and standardization in the field of modern driving automation systems. Manufacturers are allowed to choose the way of informing the driver about the need to intervene in a situation when the vehicle is unable to continue driving in automated mode. The authors proposed to assess the comprehension of the information displayed by several different icons used to inform the driver about the need to take control. For this purpose, they used the adapted ISO 9186 Comprehension Test. The research was carried out on two different groups of drivers—passenger car drivers and professional bus drivers. A total of nine different pictograms were tested. The results indicate that drivers associate the red color with information about danger. The same icon in different colors may have a different effect on drivers, often leading to wrong responses.

The rapid introduction of Advanced Driver Assistance Systems (ADAS) poses a unique challenge for older drivers, who often face barriers in adopting these technologies. This study evaluates the effectiveness of a practical, simulator-based training concept designed specifically for drivers aged 50+. The empirical analysis of a research group of 25 people focused on verifying four research hypotheses regarding the suitability of the simulator, trust calibration, user awareness, and training utility. The results confirmed that the high-fidelity simulator is an appropriate training environment for this demographic; analysis of the Revised Simulator Sickness Questionnaire (RSSQ) revealed a statistically significant reduction in symptoms during the adaptation process, validating the physical feasibility of the training (H1). The intervention led to a measurable increase in trust towards ADAS, with a strong effect size, confirming positive behavioral adaptation (H2). Furthermore, participants demonstrated raised awareness of system benefits, primarily identifying enhanced safety and speed control (H3). The proposed training model achieved high internal consistency and received positive subjective usability ratings (H4). These findings support the deployment of simulatorbased practical training as an effective tool for preventing digital exclusion among older drivers. Key words: driver training; ADAS; simulation sickness; older drivers; trust calibration.

The article presents results of an analysis of metadata structures used to describe test scenarios for automated vehicles in selected research initiatives and international standards. The paper examines approaches used in projects such as SYNERGIES, PEGASUS, and CETRAN, ISO 21448 (SOTIF) and OpenSCENARIO standards, as well as in the regulatory documents such as Highway Capacity Manual (HCM) 2000 and the NHTSA Standing General Order on Crash Reporting. The comparison reveals common metadata elements, such as descriptions of weather conditions, road infrastructure characteristics, road users, and event dynamics, which form the basis for modelling test scenarios. At the same time, significant differences resulting from different objectives—from technical validation and simulation to reporting on real-world events—are identified. The SYNERGIES project stands out with its focus on data quality, interoperability, and traceability mechanisms, making it a key step towards harmonizing the European scenario data ecosystem. The analysis results confirm the need to develop an integrated metadata model that will enable the consistent use of scenarios in the research, testing, and certification processes of automated vehicles.