Statistical Modelling of Driving Scenarios in Road Traffic using Fleet Data of Production Vehicles

Ensuring the safety of road vehicles at an acceptable level requires the absence of any unreasonable risk arising from all potential hazards linked to the intended automated driving function and its implementation. The assurance that there are no unreasonable risks stemming from hazardous behaviours associated to functional insufficiencies is denoted as safety of intended functionality (SOTIF), a concept outlined in the ISO 21448 standard. In this context, the acquisition of real driving data is considered essential for the verification and validation. For this purpose, we are currently developing a method with which data collected representatively from production vehicles can be modelled into a knowledge-based system in the future. A system that represents the probabilities of occurrence of concrete driving scenarios over the statistical population of road traffic and makes them usable. The method includes the qualitative and quantitative abstraction of the drives recorded by the sensors in the vehicles, the possibility of subsequent wireless transmission of the abstracted data from the vehicles and the derivation of the distributions and correlations of scenario parameters. This paper provides a summary of the research project and outlines its central idea. To this end, among other things, the needs for statistical information and data from road traffic are elaborated from ISO 21448, the current state of research is addressed, and methodical aspects are discussed.