An LLM with ego-centric prompts detects collisions and generates adversarial driving scenarios more reliably than Cartesian prompts, though validation of generation is limited.
A new taxonomy for automated driving: Structuring applications based on their operational design domain, level of automation and automation readiness,
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From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios
An LLM with ego-centric prompts detects collisions and generates adversarial driving scenarios more reliably than Cartesian prompts, though validation of generation is limited.