From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction
Accurate and reliable vehicle trajectory prediction is essential for safe autonomous driving. Recent studies have incorporated safety risk into trajectory prediction to quantify dangers posed by surrounding agents. However, most risk-aware approaches use past risk information as a secondary signal to help guide decisions, overlooking its future evolution and uncertainty. In this paper, we propose a risk horizon profiling (RHP) module that incorporates a continuous, learnable potential field model for risk-aware trajectory prediction. The RHP module calculates the spatial-temporal proximity of surrounding objects to profile risk distributions across future horizons, which supports better t...
| Authors | Xinyi Ning, Zilin Bian, Dachuan Zuo et al. |
|---|---|
| Primary category | cs.RO |
| Published | 30 May 2026 |
| Last updated at source | 30 May 2026 |
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