# Risk Assessment for the Development of Emergency Scenarios for Tram Driver Training
## 2 Theoretical Background
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Name** & **Description** \\ \hline VR Motion Corp—RealDrive System [9] & A portable and cost-effective VR system that enables practical driver training in a controlled environment, offering realistic scenarios and high skill retention rates (the ability of trainees to retain and apply the skills they have learned over an extended period after training). \\ \hline DReyeVR [10] & The system has been developed as an open tool for behavioral research. It allows dynamic scenario management, eye movement monitoring, and analysis of driver interaction in VR, making it a valuable tool for simulation and behavioral interaction research. \\ \hline iDrive [11] & Desktop simulators for driver education. iDrive offers advanced simulators based on high-resolution screens and physical controls, allowing driving lessons to be taught in various conditions that are difficult to replicate in reality, increasing safety and reducing training costs. \\ \hline DriveWise [12] & DriveWise has developed advanced VR simulators that offer an immersive and realistic driving learning experience. These simulators allow the environment to be tailored to specific needs, enabling participants to practice driving in various road and weather conditions that are difficult to replicate in actual driving. DriveWise also simulates emergency situations, allowing drivers to learn in a safe environment and improve their defensive skills and hazard perception. The ability to record and analyze data during the simulation allows instructors to provide effective feedback and improve participants’ skills. \\ \hline AVRT [13] & The system allows for realistic replication of emergencies in interactive scenarios, which is particularly useful in training emergency services and professional drivers. AVRT is distinguished by the ability to fully customize scenarios to meet specific training needs and record participant reactions, allowing accurate assessment of skills and identifying areas for improvement. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Examples of virtual reality environments. Figure 2: Virtual reality training system (based on [8]). The development and implementation of a VR training system is a complex process. Usually, two phases are distinguished (preparatory and training), which consist of four stages of implementation, including system design (preparation), execution, implementation, and training. It is worth noting that most publications on the use of VR technology focus on the training phase. Issues concerning the work required in the preparation phase are less popular, even though the actual implementation of the tasks performed in the system during the training phase depends on them. Therefore, the research presented in [14], in which the authors proposed a new approach to preparing a VR training system for maintenance workers, deserves attention. Their proposed scope of tasks in the preparation phase is shown in Figure 3. Based on their results, it is possible to define guidelines for the individual tasks performed in the preparation and execution phase of the VR training system. In the preparation phase of the training system, two tasks can be distinguished [14]: (1) preparation of the model and (2) creation of working instructions. The prepared model is supposed to reproduce the reality in which the training tasks will be implemented. Therefore, it becomes necessary to design the behavior of the individual components of the system and the relationships between them. The components of the system may be other participants in the process, but also 'inanimate' elements. The correctness of the prepared model determines the level of immersion achieved. Then, the module for creating work instructions focuses primarily on describing the process and the sequence of actions to be taken. For this task, it makes sense to include an expert in the research work to assess the correctness of the mapped process.