mlsanityData to 7 Oct 2026

Explainable Object-induced Action Decision for Autonomous Vehicles

arXiv 2003.09405 ↗First posted 20 Mar 2020cs.CVcited by 88

Not on the map. Why?

Cited by 22 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

A new paradigm is proposed for autonomous driving. The new paradigm lies between the end-to-end and pipelined approaches, and is inspired by how humans solve the problem. While it relies on scene understanding, the latter only considers objects that could originate hazard. These are denoted as action-inducing, since changes in their state should trigger vehicle actions. They also define a set of explanations for these actions, which should be produced jointly with the latter. An extension of the BDD100K dataset, annotated for a set of 4 actions and 21 explanations, is proposed. A new multi-task formulation of the problem, which optimizes the accuracy of both action commands and explanations, is then introduced. A CNN architecture is finally proposed to solve this problem, by combining reasoning about action inducing objects and global scene context. Experimental results show that the requirement of explanations improves the recognition of action-inducing objects, which in turn leads to better action predictions.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Mar 2020.

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Citing papers per year: 2021: 10; 2022: 8; 2023: 14; 2024: 24; 2025: 22; 2026: 10.

88 papers.

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  1. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  2. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Modelscited by 482
  3. 2022From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AIcited by 299
  4. 2022DRAMA: Joint Risk Localization and Captioning in Drivingcited by 125
  5. 2023Vision Language Models in Autonomous Driving: A Survey and Outlookcited by 124
  6. 2025Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectivescited by 120
  7. 2023Concept-based Explainable Artificial Intelligence: A Surveycited by 97
  8. 2021Explainability of deep vision-based autonomous driving systems: Review and challengescited by 80
  9. 2021Explanations in Autonomous Driving: A Surveycited by 80
  10. 2022Concept Bottleneck Model with Additional Unsupervised Conceptscited by 79
  11. 2024CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Drivingcited by 74
  12. 2021Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directionscited by 73
38 more
  1. 2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
  2. 2023Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcutscited by 63
  3. 2023Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoningcited by 63
  4. 2024Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Reviewcited by 52
  5. 2023Adversarial Counterfactual Visual Explanationscited by 47
  6. 2021STEEX: Steering Counterfactual Explanations with Semanticscited by 40
  7. 2024A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspectivecited by 37
  8. 2024BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcutscited by 36
  9. 2023Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsalcited by 33
  10. 2024RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Drivingcited by 30
  11. 2022OCTET: Object-aware Counterfactual Explanationscited by 28
  12. 2023WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributescited by 22
  13. 2024Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Drivingcited by 22
  14. 2024ROADWork: A Dataset and Benchmark for Learning to Recognize, Observe, Analyze and Drive Through Work Zonescited by 20
  15. 2025VRU-Accident: A Vision-Language Benchmark for Video Question Answering and Dense Captioning for Accident Scene Understandingcited by 20
  16. 2023Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embeddingcited by 19
  17. 2024A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcutscited by 19
  18. 2025A Comprehensive Survey on Self-Interpretable Neural Networkscited by 18
  19. 2021PSI: A Benchmark for Human Interpretation and Response in Traffic Interactionscited by 17
  20. 2025STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Drivingcited by 17
  21. 2023Explaining Autonomous Driving Actions with Visual Question Answeringcited by 16
  22. 2025Embodied Scene Understanding for Vision Language Models via MetaVQAcited by 16
  23. 2025RoadSocial: A Diverse VideoQA Dataset and Benchmark for Road Event Understanding from Social Video Narrativescited by 15
  24. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  25. 2025SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generationcited by 14
  26. 2024Large Language Models Powered Context-aware Motion Prediction in Autonomous Drivingcited by 13
  27. 2024IDD-X: A Multi-View Dataset for Ego-relative Important Object Localization and Explanation in Dense and Unstructured Trafficcited by 13
  28. 2025Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lenscited by 13
  29. 2025Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video Understandingcited by 13
  30. 2025Neurosymbolic Diffusion Modelscited by 12
  31. 2024Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Surveycited by 11
  32. 2025A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfactioncited by 11
  33. 2026SteerVLA: Steering Vision-Language-Action Models in Long-Tail Driving Scenarioscited by 11
  34. 2025DriveQA: Passing the Driving Knowledge Testcited by 10
  35. 2021Development and testing of an image transformer for explainable autonomous driving systemscited by 9
  36. 2022C-SENN: Contrastive Self-Explaining Neural Networkcited by 9
  37. 2022From Spoken Thoughts to Automated Driving Commentary: Predicting and Explaining Intelligent Vehicles' Actionscited by 8
  38. 2022Deep Learning based Computer Vision Methods for Complex Traffic Environments Perception: A Reviewcited by 7

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