1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey
April 21, 2023 Β· The Cartographer Β· π 2023 IEEE Intelligent Vehicles Symposium (IV)
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"Title-pattern auto-detect: 1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey"
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Authors
Barbara SchΓΌtt, Joshua Ransiek, Thilo Braun, Eric Sax
arXiv ID
2304.10850
Category
cs.RO: Robotics
Cross-listed
cs.SE
Citations
26
Venue
2023 IEEE Intelligent Vehicles Symposium (IV)
Last Checked
2 days ago
Abstract
Scenario generation is one of the essential steps in scenario-based testing and, therefore, a significant part of the verification and validation of driver assistance functions and autonomous driving systems. However, the term scenario generation is used for many different methods, e.g., extraction of scenarios from naturalistic driving data or variation of scenario parameters. This survey aims to give a systematic overview of different approaches, establish different categories of scenario acquisition and generation, and show that each group of methods has typical input and output types. It shows that although the term is often used throughout literature, the evaluated methods use different inputs and the resulting scenarios differ in abstraction level and from a systematical point of view. Additionally, recent research and literature examples are given to underline this categorization.
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