Incorporating Human Factors into Scenario Languages for Automated Driving Systems

Abstract

Scenario-based testing for automated driving systems (ADS) is an industry norm for safety assurance. A scenario describes situations that an automated driving systems may encounter during its operation. To ensure accurate representation of real-world situations, including human behavior and system interactions, a formal language is essential. It ensures consistent testing across diverse scenarios and facilitates compatibility with simulation tools. However, while existing scenario languages excel in describing environmental and road structure aspects, they lack the same detail for road users and drivers. We have developed a methodology to identify and incorporate relevant human factors elements into scenario languages. Our methodology focuses on understanding diverse individuals and their interactions with ADS on the road, enabling their representation in scenarios. We offer practical examples to improve language representation of human elements and actions, in WMG-SDL Level-2 for logical scenarios and BSI Flex 1889 for abstract scenario descriptions. This methodology serves as a starting point for language designers to accurately represent all road users and their interactions with ADS.