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Anomaly Detection in Autonomous Driving: A Survey

arXiv 2204.07974 ↗First posted 17 Apr 2022cs.ROcited by 87

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Abstract (arXiv)

Nowadays, there are outstanding strides towards a future with autonomous vehicles on our roads. While the perception of autonomous vehicles performs well under closed-set conditions, they still struggle to handle the unexpected. This survey provides an extensive overview of anomaly detection techniques based on camera, lidar, radar, multimodal and abstract object level data. We provide a systematization including detection approach, corner case level, ability for an online application, and further attributes. We outline the state-of-the-art and point out current research gaps.

Key facts. Cited by 87 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Apr 2022.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 4; 2023: 24; 2024: 18; 2025: 27; 2026: 14.

87 papers.

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  1. 2023DETRs Beat YOLOs on Real-time Object Detectioncited by 526
  2. 2024YOLOv10: Real-Time End-to-End Object Detectioncited by 508
  3. 2025YOLOv12: Attention-Centric Real-Time Object Detectorscited by 300
  4. 2023NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenariocited by 258
  5. 2023LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusioncited by 80
  6. 2024A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospectcited by 69
  7. 2022A Survey on Explainable Anomaly Detectioncited by 39
  8. 2023An Interactively Reinforced Paradigm for Joint Infrared-Visible Image Fusion and Saliency Object Detectioncited by 36
  9. 2025YOLOE: Real-Time Seeing Anythingcited by 36
  10. 2024VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Modelscited by 24
  11. 2023Segment Every Out-of-Distribution Objectcited by 21
  12. 2023Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?cited by 20
38 more
  1. 2023Perception Datasets for Anomaly Detection in Autonomous Driving: A Surveycited by 16
  2. 2023Towards Trustworthy Dataset Distillationcited by 14
  3. 2023NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generationcited by 14
  4. 2024AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Drivingcited by 14
  5. 2023Contracting Skeletal Kinematics for Human-Related Video Anomaly Detectioncited by 13
  6. 2025OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detectioncited by 13
  7. 2025Flashback: Memory-Driven Zero-shot, Real-time Video Anomaly Detectioncited by 12
  8. 2024Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantificationcited by 11
  9. 2023Deep Transfer Learning for Intelligent Vehicle Perception: a Surveycited by 10
  10. 2023Calibrated Out-of-Distribution Detection with a Generic Representationcited by 8
  11. 2025HiProbe-VAD: Video Anomaly Detection via Hidden States Probing in Tuning-Free Multimodal LLMscited by 8
  12. 2023Exploring the Potential of World Models for Anomaly Detection in Autonomous Drivingcited by 7
  13. 2023LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesiscited by 7
  14. 2025OCCUQ: Exploring Efficient Uncertainty Quantification for 3D Occupancy Predictioncited by 6
  15. 2022ADPS: Asymmetric Distillation Post-Segmentation for Image Anomaly Detectioncited by 5
  16. 2023Self-Aware Trajectory Prediction for Safe Autonomous Drivingcited by 5
  17. 2024Evaluation of Out-of-Distribution Detection Performance on Autonomous Driving Datasetscited by 5
  18. 2025Segmenting Objectiveness and Task-awareness Unknown Region for Autonomous Drivingcited by 5
  19. 2022Multimodal Detection of Unknown Objects on Roads for Autonomous Drivingcited by 4
  20. 2024System Safety Monitoring of Learned Components Using Temporal Metric Forecastingcited by 4
  21. 2024Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphscited by 4
  22. 2025We Need to Rethink Benchmarking in Anomaly Detectioncited by 4
  23. 2025Knowledge Regularized Negative Feature Tuning of Vision-Language Models for Out-of-Distribution Detectioncited by 4
  24. 2025A Survey on Video Anomaly Detection via Deep Learning: Human, Vehicle, and Environmentcited by 4
  25. 2023Model Monitoring and Robustness of In-Use Machine Learning Models: Quantifying Data Distribution Shifts Using Population Stability Indexcited by 3
  26. 2024UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Drivingcited by 3
  27. 2024Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errorscited by 3
  28. 2025Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detectioncited by 3
  29. 2025Mcity Data Engine: Iterative Model Improvement Through Open-Vocabulary Data Selectioncited by 3
  30. 2025CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environmentscited by 3
  31. 2025VLMDiff: Leveraging Vision-Language Models for Multi-Class Anomaly Detection with Diffusioncited by 3
  32. 2023Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenescited by 2
  33. 2023A Metacognitive Approach to Out-of-Distribution Detection for Segmentationcited by 2
  34. 2023Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuningcited by 2
  35. 2024Integrating End-to-End and Modular Driving Approaches for Online Corner Case Detection in Autonomous Drivingcited by 2
  36. 2024Out-of-Distribution Detection with Relative Anglescited by 2
  37. 2024Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directionscited by 2
  38. 2025Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbationcited by 2

50 most cited of 87 All 87 (JSON)