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Commonsense Reasoning-Aided Autonomous Vehicle Systems

arXiv 2502.09233 ↗First posted 13 Feb 2025cs.AIcited by 0

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Abstract (arXiv)

Autonomous Vehicle (AV) systems have been developed with a strong reliance on machine learning techniques. While machine learning approaches, such as deep learning, are extremely effective at tasks that involve observation and classification, they struggle when it comes to performing higher level reasoning about situations on the road. This research involves incorporating commonsense reasoning models that use image data to improve AV systems. This will allow AV systems to perform more accurate reasoning while also making them more adjustable, explainable, and ethical. This paper will discuss the findings so far and motivate its direction going forward.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 6 of its 18 references that are in the map. First posted on arXiv 13 Feb 2025.

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6 of 18 references.

References · 6

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  2. 2015VQA: Visual Question Answeringcited by 2,489
  3. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  4. 2020Neurosymbolic Reinforcement Learning with Formally Verified Explorationcited by 49
  5. 2020Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semanticscited by 15
  6. 2021AUTO-DISCERN: Autonomous Driving Using Common Sense Reasoningcited by 14

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  1. 2026Correcting Autonomous Driving Object Detection Misclassifications with Automated Commonsense Reasoning
  2. 2021Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions
  3. 2026Commonsense Reasoning in Computer Vision: Foundations, Recent Advancements, and Future Directions
  4. 2024Hybrid Reasoning Based on Large Language Models for Autonomous Car Driving
  5. 2023Benchmarks for Automated Commonsense Reasoning: A Survey
  6. 2023Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving
  7. 2026nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving
  8. 2026MoRAL: Sensor-Grounded BEV Reasoning for Compact VLMs toward Edge-Oriented Autonomous Driving