mlsanityData to 7 Oct 2026

What-If Motion Prediction for Autonomous Driving

arXiv 2008.10587 ↗First posted 24 Aug 2020cs.LG stat.MLcited by 80

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Abstract (arXiv)

Forecasting the long-term future motion of road actors is a core challenge to the deployment of safe autonomous vehicles (AVs). Viable solutions must account for both the static geometric context, such as road lanes, and dynamic social interactions arising from multiple actors. While recent deep architectures have achieved state-of-the-art performance on distance-based forecasting metrics, these approaches produce forecasts that are predicted without regard to the AV's intended motion plan. In contrast, we propose a recurrent graph-based attentional approach with interpretable geometric (actor-lane) and social (actor-actor) relationships that supports the injection of counterfactual geometric goals and social contexts. Our model can produce diverse predictions conditioned on hypothetical or "what-if" road lanes and multi-actor interactions. We show that such an approach could be used in the planning loop to reason about unobserved causes or unlikely futures that are directly relevant to the AV's intended route.

Key facts. Cited by 80 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 19; 2022: 19; 2023: 26; 2024: 13; 2025: 1; 2026: 2.

80 papers.

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  1. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  2. 2021DenseTNT: End-to-end Trajectory Prediction from Dense Goal Setscited by 292
  3. 2022Wayformer: Motion Forecasting via Simple & Efficient Attention Networkscited by 279
  4. 2021MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Predictioncited by 246
  5. 2023MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusioncited by 210
  6. 2021Multimodal Motion Prediction with Stacked Transformerscited by 207
  7. 2021Scene Transformer: A unified architecture for predicting multiple agent trajectoriescited by 165
  8. 2023MotionLM: Multi-Agent Motion Forecasting as Language Modelingcited by 154
  9. 2021GOHOME: Graph-Oriented Heatmap Output for future Motion Estimationcited by 146
  10. 2021Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Predictioncited by 131
  11. 2021HOME: Heatmap Output for future Motion Estimationcited by 122
  12. 2021LaneRCNN: Distributed Representations for Graph-Centric Motion Forecastingcited by 112
38 more
  1. 2021Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversalscited by 112
  2. 2021THOMAS: Trajectory Heatmap Output with learned Multi-Agent Samplingcited by 101
  3. 2022M2I: From Factored Marginal Trajectory Prediction to Interactive Predictioncited by 81
  4. 2023Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoderscited by 72
  5. 2021LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agentscited by 64
  6. 2023LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraintscited by 50
  7. 2022JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Drivingcited by 40
  8. 2021Vehicle trajectory prediction works, but not everywherecited by 39
  9. 2023ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptationcited by 39
  10. 2021Divide-and-Conquer for Lane-Aware Diverse Trajectory Predictioncited by 37
  11. 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 32
  12. 2022SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Drivingcited by 31
  13. 2023The Integration of Prediction and Planning in Deep Learning Automated Driving Systems: A Reviewcited by 29
  14. 2023WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecastingcited by 28
  15. 2023Dynamic Scenario Representation Learning for Motion Forecasting with Heterogeneous Graph Convolutional Recurrent Networkscited by 27
  16. 2022CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attentioncited by 21
  17. 2022CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationshipscited by 18
  18. 2023SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networkscited by 18
  19. 2022StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Drivingcited by 14
  20. 2023Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environmentscited by 14
  21. 2021Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Predictioncited by 12
  22. 2022Diverse Multiple Trajectory Prediction Using a Two-stage Prediction Network Trained with Lane Losscited by 12
  23. 2022RAP: Risk-Aware Prediction for Robust Planningcited by 12
  24. 2023Context-Aware Timewise VAEs for Real-Time Vehicle Trajectory Predictioncited by 12
  25. 2024MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Drivingcited by 12
  26. 2021Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modelingcited by 11
  27. 2022TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictorcited by 10
  28. 2022Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecastingcited by 10
  29. 2022Towards Explainable Motion Prediction using Heterogeneous Graph Representationscited by 10
  30. 2023Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction using Diffusion Graph Convolutional Networkscited by 10
  31. 2023Interactive Autonomous Navigation with Internal State Inference and Interactivity Estimationcited by 10
  32. 2024SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction using Knowledge Graphscited by 10
  33. 2021Self-Supervised Action-Space Prediction for Automated Drivingcited by 9
  34. 2022Interventional Behavior Prediction: Avoiding Overly Confident Anticipation in Interactive Predictioncited by 8
  35. 2022Exploiting map information for self-supervised learning in motion forecastingcited by 8
  36. 2024MoST: Multi-modality Scene Tokenization for Motion Predictioncited by 8
  37. 2022Context-Aware Scene Prediction Network (CASPNet)cited by 7
  38. 2023Bridging the Gap Between Multi-Step and One-Shot Trajectory Prediction via Self-Supervisioncited by 7

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