mlsanityData to 7 Oct 2026

DRAMA: An Efficient End-to-end Motion Planner for Autonomous Driving with Mamba

arXiv 2408.03601 ↗First posted 7 Aug 2024cs.ROcited by 87

On the map: End-to-end autonomous driving → End-to-end system architecture

also in 1 more
Abstract (arXiv)

Motion planning is a challenging task to generate safe and feasible trajectories in highly dynamic and complex environments, forming a core capability for autonomous vehicles. In this paper, we propose DRAMA, the first Mamba-based end-to-end motion planner for autonomous vehicles. DRAMA fuses camera, LiDAR Bird's Eye View images in the feature space, as well as ego status information, to generate a series of future ego trajectories. Unlike traditional transformer-based methods with quadratic attention complexity for sequence length, DRAMA is able to achieve a less computationally intensive attention complexity, demonstrating potential to deal with increasingly complex scenarios. Leveraging our Mamba fusion module, DRAMA efficiently and effectively fuses the features of the camera and LiDAR modalities. In addition, we introduce a Mamba-Transformer decoder that enhances the overall planning performance. This module is universally adaptable to any Transformer-based model, especially for tasks with long sequence inputs. We further introduce a novel feature state dropout which improves the planner's robustness without increasing training and inference times. Extensive experimental results show that DRAMA achieves higher accuracy on the NAVSIM dataset compared to the baseline Transfuser, with fewer parameters and lower computational costs.

Key facts. Cited by 87 papers in the map (data through 7 Oct 2026). Placed in End-to-end system architecture, one of 9 directions in End-to-end autonomous driving. Builds on 27 of its 41 references that are in the map. First posted on arXiv 7 Aug 2024.

Builds on

27 of 41 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking21 Jun
  2. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving31 May
  3. 2021NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles22 Jun

Other references · 24

  1. 2021Masked Autoencoders Are Scalable Vision Learnerscited by 7,339
  2. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  3. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  4. 2024Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Dualitycited by 1,283
  5. 2022Planning-oriented Autonomous Drivingcited by 1,068
  6. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,051
  7. 2024Jamba: A Hybrid Transformer-Mamba Language Modelcited by 390
  8. 2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 267
  9. 2016A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehiclescited by 251
  10. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  11. 2023Parting with Misconceptions about Learning-based Vehicle Motion Planningcited by 238
  12. 2021Multimodal Motion Prediction with Stacked Transformerscited by 207
12 more
  1. 2023GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Drivingcited by 141
  2. 2023MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Queryingcited by 139
  3. 2024Motion Mamba: Efficient and Long Sequence Motion Generationcited by 111
  4. 2018Baidu Apollo EM Motion Plannercited by 99
  5. 2024PLUTO: Pushing the Limit of Imitation Learning-based Planning for Autonomous Drivingcited by 84
  6. 2024MoE-Mamba: Efficient Selective State Space Models with Mixture of Expertscited by 60
  7. 2023DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Drivingcited by 46
  8. 2023Rethinking Imitation-based Planner for Autonomous Drivingcited by 25
  9. 2024DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Modelscited by 22
  10. 2023Imitation with Spatial-Temporal Heatmap: 2nd Place Solution for NuPlan Challengecited by 19
  11. 2024ControlMTR: Control-Guided Motion Transformer with Scene-Compliant Intention Points for Feasible Motion Predictioncited by 13
  12. 2022GET-DIPP: Graph-Embedded Transformer for Differentiable Integrated Prediction and Planningcited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 37; 2026: 48.

87 papers.

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  1. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
  2. 2025AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuningcited by 252
  3. 2025ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Drivingcited by 190
  4. 2025End-to-End Driving with Online Trajectory Evaluation via BEV World Modelcited by 145
  5. 2025Epona: Autoregressive Diffusion World Model for Autonomous Drivingcited by 115
  6. 2025DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planningcited by 91
  7. 2025ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Drivingcited by 66
  8. 2025AdaThinkDrive: Adaptive Thinking via Reinforcement Learning for Autonomous Drivingcited by 57
  9. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Drivingcited by 52
  10. 2024V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Modelscited by 47
  11. 2025iPad: Iterative Proposal-centric End-to-End Autonomous Drivingcited by 41
  12. 2025Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Trainingcited by 39
38 more
  1. 2025DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Drivingcited by 39
  2. 2026Driving on Registerscited by 38
  3. 2026SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Drivingcited by 34
  4. 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 32
  5. 2025From Forecasting to Planning: Policy World Model for Collaborative State-Action Predictioncited by 29
  6. 2025BEVDriver: Leveraging BEV Maps in LLMs for Robust Closed-Loop Drivingcited by 26
  7. 2025ImagiDrive: A Unified Imagination-and-Planning Framework for Autonomous Drivingcited by 24
  8. 2026SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Drivingcited by 21
  9. 2025Reinforced Refinement with Self-Aware Expansion for End-to-End Autonomous Drivingcited by 19
  10. 2026VGGDrive: Empowering Vision-Language Models with Cross-View Geometric Grounding for Autonomous Drivingcited by 19
  11. 2025PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Drivingcited by 16
  12. 2026SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Modelcited by 15
  13. 2026DriveFuture: Future-Aware Latent World Models for Autonomous Drivingcited by 15
  14. 2025InsightDrive: Insight Scene Representation for End-to-End Autonomous Drivingcited by 14
  15. 2026ResWorld: Temporal Residual World Model for End-to-End Autonomous Drivingcited by 14
  16. 2026DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Drivingcited by 13
  17. 2026AutoDrive-P3: Unified Chain of Perception-Prediction-Planning Thought via Reinforcement Fine-Tuningcited by 13
  18. 2025EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Drivingcited by 12
  19. 2025ResAD: Normalized Residual Trajectory Modeling for End-to-End Autonomous Drivingcited by 12
  20. 2025MindDrive: An All-in-One Framework Bridging World Models and Vision-Language Model for End-to-End Autonomous Drivingcited by 12
  21. 2025WAM-Diff: A Masked Diffusion VLA Framework with MoE and Online Reinforcement Learning for Autonomous Drivingcited by 10
  22. 2026ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Drivingcited by 10
  23. 2026Metis: A Generalizable and Efficient World-Action Model for Autonomous Driving and Urban Navigationcited by 10
  24. 2026Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation Systemcited by 10
  25. 2025DiffE2E: Rethinking End-to-End Driving with a Hybrid Action Diffusion and Supervised Policycited by 9
  26. 2025Percept-WAM: Perception-Enhanced World-Awareness-Action Model for Robust End-to-End Autonomous Drivingcited by 9
  27. 2026DriveMamba: Task-Centric Scalable State Space Model for Efficient End-to-End Autonomous Drivingcited by 9
  28. 2026CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planningcited by 9
  29. 2025DRAE: Dynamic Retrieval-Augmented Expert Networks for Lifelong Learning and Task Adaptation in Roboticscited by 8
  30. 2026Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Drivingcited by 8
  31. 2025FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Modelcited by 7
  32. 2026Test-Time Trajectory Optimization for Autonomous Drivingcited by 7
  33. 2025Fully Unified Motion Planning for End-to-End Autonomous Drivingcited by 6
  34. 2026GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Drivingcited by 6
  35. 2026HAD: Combining Hierarchical Diffusion with Metric-Decoupled RL for End-to-End Drivingcited by 4
  36. 2026ProDrive: Proactive Planning for Autonomous Driving via Ego-Environment Co-Evolutioncited by 4
  37. 2025Generative AI for Autonomous Driving: A Reviewcited by 3
  38. 2025Echo Planning for Autonomous Driving: From Current Observations to Future Trajectories and Backcited by 3

50 most cited of 87 All 87 (JSON)

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  1. 2021End-to-end Interpretable Neural Motion Planner
  2. 2025MTR-VP: Towards End-to-End Trajectory Planning through Context-Driven Image Encoding and Multiple Trajectory Prediction
  3. 2025HAMF: A Hybrid Attention-Mamba Framework for Joint Scene Context Understanding and Future Motion Representation Learning
  4. 2025Trajectory Mamba: Efficient Attention-Mamba Forecasting Model Based on Selective SSM
  5. 2025Using Ensemble Diffusion to Estimate Uncertainty for End-to-End Autonomous Driving
  6. 2026Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms
  7. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networks
  8. 2024MambaBEV: An EV-based 3D detection model with Mamba2