1001 Ways of Scenario Generation for Testing of Self-driving Cars: A Survey

April 21, 2023 Β· The Cartographer Β· πŸ› 2023 IEEE Intelligent Vehicles Symposium (IV)

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Survey/review paper β€” maps the landscape rather than implementing a method.

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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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