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The advent of Advanced Driver Assistance Systems (ADAS) and automated driving has offered a new challenge for functional verification and validation. The explosion of the test sample space for possible combinations of inputs needs to be handled in an intelligent manner to meet cost and time targets for the development of such systems. This paper addresses this research gap by using constrained randomization techniques for the creation of the required test scenarios and test cases. Furthermore, this paper proposes an automated constrained randomized test scenario generation framework for testing of ADAS and automated systems in a driving simulator setup. The constrained randomization approach is deployed at two levels: 1) test scenario randomization 2) test case randomization. The novelty of the proposed approach is in applying the constrained randomization method to generate test scenarios and test cases for automotive system and system of systems in a driving simulator environment.

Increasing automation in the automotive systems has re-focused the industry’s attention on verification and validation methods and especially on the development of test scenarios. The complex nature of Advanced Driver Assistance Systems (ADASs) and Automated Driving (AD) systems warrant the adoption of new and innovative means of evaluating and establishing the safety of such systems. In this paper, the authors discuss the results from a semi-structured interview study, which involved interviewing ADAS and AD experts across the industry supply chain. Eighteen experts (each with over 10 years’ of experience in testing and development of automotive systems) from different countries were interviewed on two themes: test methods and test scenarios. Each of the themes had three guiding questions which had some follow-up questions. The interviews were transcribed and a thematic analysis via coding was conducted on the transcripts.