mlsanityData to 14 Oct 2026

Grounded Relational Inference: Domain Knowledge Driven Explainable Autonomous Driving

arXiv 2102.11905 ↗First posted 23 Feb 2021cs.AI cs.LG cs.ROcited by 6

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Abstract (arXiv)

Explainability is essential for autonomous vehicles and other robotics systems interacting with humans and other objects during operation. Humans need to understand and anticipate the actions taken by the machines for trustful and safe cooperation. In this work, we aim to develop an explainable model that generates explanations consistent with both human domain knowledge and the model's inherent causal relation. In particular, we focus on an essential building block of autonomous driving, multi-agent interaction modeling. We propose Grounded Relational Inference (GRI). It models an interactive system's underlying dynamics by inferring an interaction graph representing the agents' relations. We ensure a semantically meaningful interaction graph by grounding the relational latent space into semantic interactive behaviors defined with expert domain knowledge. We demonstrate that it can model interactive traffic scenarios under both simulation and real-world settings, and generate semantic graphs explaining the vehicle's behavior by their interactions.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 34 of its 52 references that are in the map. First posted on arXiv 23 Feb 2021.

Builds on

34 of 52 references.

References · 34

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22 more
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Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 2.

6 papers.

  1. 2023Towards Knowledge-driven Autonomous Drivingcited by 29
  2. 2024Disentangled Neural Relational Inference for Interpretable Motion Predictioncited by 7
  3. 2024Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmapcited by 6
  4. 2022DIDER: Discovering Interpretable Dynamically Evolving Relationscited by 2
  5. 2025Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profilescited by 0
  6. 2025Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Modelscited by 0