mlsanityData to 7 Oct 2026

Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking

arXiv 2410.08616 ↗First posted 11 Oct 2024cs.ROcited by 5

On the map: Multimodal LLMs / vision-language models → Driving VLMs and open-vocabulary detection

Abstract (arXiv)

Automatic Emergency Braking (AEB) systems are a crucial component in ensuring the safety of passengers in autonomous vehicles. Conventional AEB systems primarily rely on closed-set perception modules to recognize traffic conditions and assess collision risks. To enhance the adaptability of AEB systems in open scenarios, we propose Dual-AEB, a system combines an advanced multimodal large language model (MLLM) for comprehensive scene understanding and a conventional rule-based rapid AEB to ensure quick response times. To the best of our knowledge, Dual-AEB is the first method to incorporate MLLMs within AEB systems. Through extensive experimentation, we have validated the effectiveness of our method. The source code will be available at https://github.com/ChipsICU/Dual-AEB.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Driving VLMs and open-vocabulary detection, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 39 of its 70 references that are in the map. First posted on arXiv 11 Oct 2024.

Builds on

39 of 70 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models19 Feb

Other references · 38

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,669
  4. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  5. 2022Planning-oriented Autonomous Drivingcited by 1,068
  6. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 677
  7. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 613
  8. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  9. 2023GPT-Driver: Learning to Drive with GPTcited by 344
  10. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  11. 2023LMDrive: Closed-Loop End-to-End Driving with Large Language Modelscited by 301
  12. 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Drivingcited by 250
26 more
  1. 2022Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baselinecited by 247
  2. 2023Parting with Misconceptions about Learning-based Vehicle Motion Planningcited by 238
  3. 2023Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Drivingcited by 231
  4. 2023Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenescited by 191
  5. 2023LanguageMPC: Large Language Models as Decision Makers for Autonomous Drivingcited by 188
  6. 2023RoCo: Dialectic Multi-Robot Collaboration with Large Language Modelscited by 171
  7. 2023Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Drivingcited by 168
  8. 2023Drive Like a Human: Rethinking Autonomous Driving with Large Language Modelscited by 158
  9. 2023DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Drivingcited by 142
  10. 2023Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?cited by 104
  11. 2023ADAPT: Action-aware Driving Caption Transformercited by 78
  12. 2023ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planningcited by 77
  13. 2023LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoningcited by 59
  14. 2024Think2Drive: Efficient Reinforcement Learning by Thinking in Latent World Model for Quasi-Realistic Autonomous Driving (in CARLA-v2)cited by 51
  15. 2024Abductive Ego-View Accident Video Understanding for Safe Driving Perceptioncited by 43
  16. 2024PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planningcited by 38
  17. 2024Lifelong Robot Library Learning: Bootstrapping Composable and Generalizable Skills for Embodied Control with Language Modelscited by 26
  18. 2018Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunitiescited by 20
  19. 2023Kinematic-aware Prompting for Generalizable Articulated Object Manipulation with LLMscited by 19
  20. 2017Autonomous Braking System via Deep Reinforcement Learningcited by 18
  21. 2023GG-LLM: Geometrically Grounding Large Language Models for Zero-shot Human Activity Forecasting in Human-Aware Task Planningcited by 13
  22. 2022Deep Learning Opacity in Scientific Discoverycited by 9
  23. 2022Pedestrian Emergency Braking in Ten Weekscited by 2
  24. 2021Intelligent Momentary Assisted Control for Autonomous Emergency Brakingcited by 1
  25. 2021Emergency-braking Distance Prediction using Deep Learningcited by 1
  26. 2023CARTIER: Cartographic lAnguage Reasoning Targeted at Instruction Execution for Robotscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Drivingcited by 28
  2. 2025Argus: Resilience-Oriented Safety Assurance Framework for End-to-End ADSscited by 1
  3. 2026Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Drivingcited by 1
  4. 2026Scaling Learning-based AEB with Massive Unlabeled Datacited by 0
  5. 2026OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMscited by 0

Similar, not cited

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  1. 2025Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends
  2. 2023A Survey on Multimodal Large Language Models for Autonomous Driving
  3. 2024Using Multimodal Large Language Models for Automated Detection of Traffic Safety Critical Events
  4. 2024Hybrid Reasoning Based on Large Language Models for Autonomous Car Driving
  5. 2025SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
  6. 2025Why Braking? Scenario Extraction and Reasoning Utilizing LLM
  7. 2024DualAD: Dual-Layer Planning for Reasoning in Autonomous Driving
  8. 2025DriveSOTIF: Advancing Perception SOTIF Through Multimodal Large Language Models