The goal of this tutorial was to demonstrate the use of a compact motion-based driving simulator intended for driver evaluation and assessment of driving performance. It covered all steps of a typical simulator-based user study, from experiment design, development of simulation environment and scenarios, integration of external sensors as well as data collection and analysis. Participants were demonstrated a professional simulation software development kit, methods and equipment that is typically used for acquisition of data on driver behavior and performance, and techniques for big data processing and analysis. They also took part in a short use case during the tutorial and discussed all of the pros and cons of performing studies in a driving simulator. The main outcome of this tutorial was a detailed overview of methods and available equipment for fast, accurate and efficient data collection on driving performance and driver behavior, as well as methods for analysis and interpretation of such diverse data.
COBISS.SI-ID: 11834708
This paper presented NERVteh as a Slovenian high-tech R&D company, specialized in vehicle simulation and driver evaluation technologies. Its main product is a compact driving simulator based on a 4DOF motion platform and powerful simulation software. It is modular and customizable software, providing a variety of virtual environments, road and weather conditions, AI-based traffic and realistic vehicle dynamics. The simulator hardware consists mostly of real car components and offers almost real-life driving experience. The simulation can run on three large curved screens or on a VR headset. Additionally, it enables real-time communication and synchronization with a set of external sensors for assessment of drivers’ physical and mental states. This technology is mostly used for driver training and education, biometrical evaluation and profiling. It is also a very efficient tool for development and testing of smart traffic infrastructure, road planning and risk assessment of drivers. This demonstration of the NERVteh driving simulator on a science conference was an excellent opportunity for the company to present itself and its product to the academic automotive community, where driving simulators are often used for development and testing of new technologies.
COBISS.SI-ID: 11834452
This paper proposes a methodology for driver behaviour evaluation in a driving simulator. The proposed methodology observes speed, acceleration, winding and safety distance as parameters for evaluation of driving performance. The proposed methodology was evaluated with a user study with 29 participants. With the collected data and the proposed methodology, 5 different driving profiles were defined, ranging from very safe to very dangerous driver. The proposed methodology can be used for simple driver profiling based on driving performance recorded in a driving simulator.
COBISS.SI-ID: 11742548