DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving

arXiv:2605.23176 · cs.CV · Submitted 2026-05-22 · Read on arXiv

cs.CV

Submitted: 2026-05-22

Updated: 2026-09-26

Project page: https://uark-aicv.github.io/DriveSpatial/Truck

Terminology

• Benchmark — 50× in this paper · explained in 2 episodes
• Autonomous Driving — 31× in this paper
• Grounding — 9× in this paper · explained in 3 episodes
• Benchmarking — 7× in this paper · explained in 3 episodes
• Temporal Reasoning — 7× in this paper · explained in 2 episodes
• Adam — 6× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Generalization — 5× in this paper · explained in 13 episodes
• Human-in-the-Loop — 4× in this paper · explained in 3 episodes
• World Model — 4× in this paper · explained in 7 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Multimodal Dataset — 2× in this paper · explained in 2 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Winter Conference on Applications of Computer Vision — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Association for the Advancement of Artificial Intelligence — 1× in this paper
• Calibration — 1× in this paper · explained in 7 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Diagnostic Tools — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Task Planning — 1× in this paper · explained in 2 episodes

Sources

• NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
• Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes
• Vision Language Models in Autonomous Driving: A Survey and Outlook
• A Survey on Multimodal Large Language Models for Autonomous Driving
• Qwen3-VL Technical Report
• Llama 2: Open Foundation and Fine-Tuned Chat Models
• GPT-4 Technical Report
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• Kimi-VL Technical Report
• DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
• Gemini: A Family of Highly Capable Multimodal Models
• Directed-Tokens: A Robust Multi-Modality Alignment Approach to Large Language-Vision Models
• GAIA-1: A Generative World Model for Autonomous Driving
• DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving
• An Empirical Analysis on Spatial Reasoning Capabilities of Large Multimodal Models
• EmbSpatial-Bench: Benchmarking Spatial Understanding for Embodied Tasks with Large Vision-Language Models
• Gemini Robotics: Bringing AI into the Physical World
• SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning
• OmniSpatial: Towards Comprehensive Spatial Reasoning Benchmark for Vision Language Models
• HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models

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