Unveiling Trust: A Model-Based Approach to Understanding and Enhancing Perceived Safety in Autonomous Vehicles

Abstract

Rapid technological development and shorter innovation cycles are driving significant changes in the field of autonomous vehicle systems. The trend towards autonomous driving has increased the importance of existing and new assistance systems in vehicles. The aim of developing such systems is to reduce the frequency and severity of accidents as traffic density increases. In addition, the presence of driver assistance systems should have a positive impact on the safety perception of vehicle occupants. At the same time, understanding human perception is becoming increasingly important as technology advances. For vehicle manufacturers, occupant safety perception is critical to improving their market position, as safety is an important decision criterion for users.The objective of this paper is to identify the factors that influence occupant and driver safety perception in Level 3 autonomous vehicles and to embed them in a comprehensive model. For this purpose, the current state of the art was reviewed and analyzed. The results were then used to identify a total of 17 factors in five categories of influence. The model shows the interrelations and dependencies between these factors. With the help of the developed model, it should be possible in the future to systematically evaluate vehicle interiors with regard to perceived safety.The developed model integrates objective factors that influence perceived safety and aims to be applicable across manufacturers and vehicle models. The model considers objective factors with measurable influences and defined optimal ranges, such as interior temperature. It is intended to serve as a basis for understanding the complex interactions that influence human perception of safety in autonomous driving scenarios.The development of a model that can be used as a basis for assessing perceived safety in autonomous vehicles proved to be complex, especially given the ongoing research in this area and the lack of fully autonomous vehicles on the market. Therefore, the model is designed to be extended in the future. Further studies are needed to improve the model, including experiments in real vehicles with different levels of autonomy and the development of appropriate measurement tools. In addition, it is important to investigate the composition of an ideal survey group, taking into account factors such as geographical origin and socio-economic background. The results of the experiments and surveys must be statistically analyzed in order to continuously improve the model. External influences, such as market trends, should be taken into account in the ongoing monitoring and improvement process.In conclusion, the developed model captures the influences on drivers and occupants of Level 3 autonomous vehicles and forms the basis for further research. Future research should focus on objective assessments using a catalog based on the model. In addition, ongoing research is essential to keep the model relevant in the face of technological advances and market dynamics.