arXiv AI
Jun 2
From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction
arXiv:2606. 00857v1 Announce Type: cross Abstract: Accurate and reliable vehicle trajectory prediction is essential for safe autonomous driving.
TrajRS: Towards Certified Robustness in Pedestrian Trajectory Prediction
arXiv:2606. 28716v1 Announce Type: new Abstract: The robustness of trajectory prediction models is crucial for developing safe autonomous driving systems.
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arXiv Machine Learning
Jul 8
Higher-Order Certified Robustness for Regression
arXiv:2607. 05536v1 Announce Type: cross Abstract: Randomized smoothing has emerged as a scalable technique for certifying the adversarial robustness of classifiers.
arXiv AI
Jun 6
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
arXiv:2606. 06423v1 Announce Type: cross Abstract: Safety-critical traffic scenario generation is essential for evaluating autonomous driving systems under rare but high-risk interactions.
arXiv Machine Learning
6d ago
Clustered Randomized Smoothing for Stochastic Prediction Functions
arXiv:2608. 12037v1 Announce Type: new Abstract: Modern stochastic predictors can model rich, multi-modal outcome distributions.
arXiv AI
Aug 5
Long-term Traffic Scene Prediction via Polynomial Representations in Autonomous Driving
arXiv:2608. 03330v1 Announce Type: new Abstract: This thesis addresses fundamental challenges in traffic scene prediction for autonomous driving by introducing robust and computationally efficient models based on polynomial representations.
arXiv Machine Learning
Aug 11
CoCoNav: Conformal Control for Safe Robot Navigation in Crowds
arXiv:2608. 07751v1 Announce Type: cross Abstract: Safe and efficient robot navigation in crowds requires anticipating pedestrian motion despite uncertain and potentially shifting prediction errors.
arXiv Machine Learning
Jun 8
Certified Robustness to Data Poisoning in Gradient-Based Training
arXiv:2406. 05670v3 Announce Type: replace Abstract: Modern machine learning pipelines leverage large amounts of public data, making it infeasible to guarantee data quality and leaving models open to poisoning and backdoor attacks.
arXiv AI
Jun 16
Is Your Trajectory Displacement Safe in Long-tail?
arXiv:2606. 16313v1 Announce Type: cross Abstract: Long-tail scenarios remain a major bottleneck for autonomous driving evaluation, even as datasets grow by orders of magnitude.
arXiv AI
Jul 28
From Camera-Based Sensing to Reasoning: A Comprehensive Review Toward Proactive Vulnerable Road User Safety
arXiv:2510. 03314v2 Announce Type: replace-cross Abstract: Ensuring the safety of vulnerable road users (VRUs), such as pedestrians and cyclists, remains a critical challenge, as conventional infrastructure-based measures are often insufficient in dynamic urban environments.
arXiv AI
Jul 29
Real-Time Driver Safety Scoring Through Inverse Crash Probability Modeling
arXiv:2603. 14841v3 Announce Type: replace-cross Abstract: Road crashes remain a leading cause of preventable fatalities.
arXiv AI
Jun 16
Driving, Fast or Slow? Neuro-Symbolic Guidance for Motion Prediction in Multi-Modal Ground Mobility
arXiv:2606. 15251v1 Announce Type: cross Abstract: Accurate and interpretable motion prediction for heterogeneous traffic spaces, including pedestrians, bicycles, cars, and trucks, is essential for safe autonomous navigation.
arXiv AI
Jun 9
Hybrid Robustness Verification for Spatio-Temporal Neural Networks
arXiv:2606. 09746v1 Announce Type: cross Abstract: With AI increasingly deployed in safety-critical systems, providing formal robustness guarantees for the underlying models is essential.