Context & Motivation

Autonomous driving systems (ADS) are complex systems requiring comprehensive testing to ensure their sufficient safety. These systems must operate reliably in dynamic, uncertain, and safety-critical environments. Traditional testing methods, such as road testing or mileage-based validation, are increasingly considered insufficient due to their inability to systematically cover the vast space of possible driving conditions and rare edge cases.

Scenario-based testing (SBT) has emerged as a promising methodology to address these limitations. It involves designing and executing driving scenarios representing both typical and critical traffic situations. While SBT is gaining traction in academic research and international standardization initiatives (e.g., ASAM OpenSCENARIO), its level of adoption in industrial practice remains unclear. There is only limited empirical evidence on how companies developing ADS integrate scenario-based approaches into their development pipelines. Understanding the adoption status is critical for identifying gaps between theory and practice and guiding future research.

This thesis aims to address this gap by surveying the current state of industrial adoption of SBT. Through a combination of literature review and empirical research, based on interviews and surveys with industry professionals, this study will explore how scenario-based testing is used to validate ADS. It will also identify common challenges, tools, organizational strategies, and success factors influencing adoption. The findings will contribute to a more complete understanding of the maturity and applicability of SBT in real-world settings.

Research questions

1. What is the current state of scenario-based testing adoption in the automotive industry?

2. What tools, frameworks, and standards are used to implement scenario-based testing in industry?

3. What are the key drivers and barriers influencing the adoption of scenario-based testing?

4. How does industrial practice compare to academic research on scenario-based testing?

Objectives

The main goal of this thesis is to investigate the current state of industrial adoption of scenario-based testing for autonomous driving systems. Specific objectives include:

• Literature review: Systematically collect relevant literature on scenario-based testing and its adoption to understand the relevant background, methodologies, and technical concepts.
• Empirical study design: Design and execute empirical methods targeting professionals working on ADS validation.
• Data analysis and interpretation: Analyze collected data to identify adoption trends, challenges, and gaps between research and practice.
• Discussion and recommendations: Highlight common barriers to SBT adoption, suggest ways to overcome them, and offer suggestions for further research.