mlsanityData to 14 Oct 2026

ComDrive: Comfort-Oriented End-to-End Autonomous Driving

arXiv 2410.05051 ↗First posted 7 Oct 2024cs.CV cs.ROcited by 11

On the map: Diffusion models → Diffusion and flow policies for robotics

also in 1 more
Abstract (arXiv)

We propose ComDrive: the first comfort-oriented end-to-end autonomous driving system to generate temporally consistent and comfortable trajectories. Recent studies have demonstrated that imitation learning-based planners and learning-based trajectory scorers can effectively generate and select safety trajectories that closely mimic expert demonstrations. However, such trajectory planners and scorers face the challenge of generating temporally inconsistent and uncomfortable trajectories. To address these issues, ComDrive first extracts 3D spatial representations through sparse perception, which then serves as conditional inputs. These inputs are used by a Conditional Denoising Diffusion Probabilistic Model (DDPM)-based motion planner to generate temporally consistent multi-modal trajectories. A dual-stream adaptive trajectory scorer subsequently selects the most comfortable trajectory from these candidates to control the vehicle. Experiments demonstrate that ComDrive achieves state-of-the-art performance in both comfort and safety, outperforming UniAD by 17% in driving comfort and reducing collision rates by 25% compared to SparseDrive. More results are available on our project page: https://jmwang0117.github.io/ComDrive/.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 40 of its 46 references that are in the map. First posted on arXiv 7 Oct 2024.

Builds on

40 of 46 references.

Closest ancestors · 5

Same direction, newest first

  1. 2023SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Execution18 Dec
  2. 2023NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration11 Oct
  3. 2023Goal-Conditioned Imitation Learning using Score-based Diffusion Policies5 Apr
  4. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar
  5. 2023Imitating Human Behaviour with Diffusion Models25 Jan

Other references · 35

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2020Denoising Diffusion Implicit Modelscited by 9,781
  4. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  5. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,234
  6. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,333
  7. 2022Planning-oriented Autonomous Drivingcited by 1,087
  8. 2022Planning with Diffusion for Flexible Behavior Synthesiscited by 1,061
  9. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 622
  10. 2023DriveLM: Driving with Graph Visual Question Answeringcited by 536
  11. 2022ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learningcited by 368
  12. 2020TNT: Target-driveN Trajectory Predictioncited by 347
23 more
  1. 2023GPT-Driver: Learning to Drive with GPTcited by 347
  2. 2024Hallucination is Inevitable: An Innate Limitation of Large Language Modelscited by 332
  3. 2023LMDrive: Closed-Loop End-to-End Driving with Large Language Modelscited by 305
  4. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 289
  5. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 249
  6. 2023Parting with Misconceptions about Learning-based Vehicle Motion Planningcited by 242
  7. 2023Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?cited by 242
  8. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 241
  9. 2023OccWorld: Learning a 3D Occupancy World Model for Autonomous Drivingcited by 233
  10. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  11. 2022Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformercited by 212
  12. 2023Scene as Occupancycited by 209
  13. 2021NEAT: Neural Attention Fields for End-to-End Autonomous Drivingcited by 174
  14. 2021A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language Modelscited by 101
  15. 2018Baidu Apollo EM Motion Plannercited by 100
  16. 2023ReasonNet: End-to-End Driving with Temporal and Global Reasoningcited by 93
  17. 2022Differentiable Raycasting for Self-supervised Occupancy Forecastingcited by 84
  18. 2024PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Drivingcited by 84
  19. 2024Potential Based Diffusion Motion Planningcited by 41
  20. 2024HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attentioncited by 38
  21. 2020Socially-Compatible Behavior Design of Autonomous Vehicles with Verification on Real Human Datacited by 18
  22. 2024DualAD: Disentangling the Dynamic and Static World for End-to-End Drivingcited by 17
  23. 2022An Efficient Spatial-Temporal Trajectory Planner for Autonomous Vehicles in Unstructured Environmentscited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 9; 2026: 1.

11 papers.

  1. 2025Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Drivingcited by 84
  2. 2025DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Drivingcited by 17
  3. 2024CALMM-Drive: Confidence-Aware Autonomous Driving with Large Multimodal Modelcited by 12
  4. 2025VDT-Auto: End-to-end Autonomous Driving with VLM-Guided Diffusion Transformerscited by 12
  5. 2025Generating Multimodal Driving Scenes via Next-Scene Predictioncited by 12
  6. 2025DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policycited by 9
  7. 2025Fully Unified Motion Planning for End-to-End Autonomous Drivingcited by 6
  8. 2025VDRive: Leveraging Reinforced VLA and Diffusion Policy for End-to-end Autonomous Drivingcited by 5
  9. 2025Edge-Based Multimodal Sensor Data Fusion with Vision Language Models (VLMs) for Real-time Autonomous Vehicle Accident Avoidancecited by 3
  10. 2026Zero-Shot Cross-City Generalization in End-to-End Autonomous Driving: Self-Supervised versus Supervised Representationscited by 3
  11. 2025DriveMRP: Enhancing Vision-Language Models with Synthetic Motion Data for Motion Risk Predictioncited by 2

Similar, not cited

Close in wording, no citation either way

  1. 2026ForeDrive: Foresight-Guided End-to-End Autonomous Driving with a Planning-Relevant Latent World Model
  2. 2025AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
  3. 2026Comfort by Construction: Adaptive, Comfort-Bounded Action Spaces for Learned Driving Policies
  4. 2026YOUDrive: Driving Style as a Composable Direction for End-to-End Autonomous Driving
  5. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Driving
  6. 2026FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving
  7. 2026Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
  8. 2026BridgeGuard: Explicit Safety Drift for Diffusion-based Autonomous Driving