Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic
The rapid advancement of autonomous driving (AD) technologies has outpaced the development of robust safety evaluation methods. Conventional testing relies on exposing AD systems to vast numbers of real-world traffic scenes -- a brute-force approach that is prohibitively expensive and statistically ineffective at capturing the rare, safety-critical edge cases essential for validating real-world robustness. To address this fundamental limitation, we introduce STRELGen, a scalable framework for the targeted generation of safety-critical driving scenarios. STRELGen synergistically combines a multi-agent trajectory-generation diffusion model (DM) with Spatio-Temporal Logic (STREL) specificati...
| Authors | Lorenzo Bonin, Francesco Giacomarra, Luca Bortolussi et al. |
|---|---|
| Primary category | cs.RO |
| Published | 18 May 2026 |
| Last updated at source | 18 May 2026 |
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