Data to 14 Oct 2026

Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving

arXiv 1808.05819 ↗First posted 17 Aug 2018cs.LG cs.CV cs.ROcited by 90

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Abstract (arXiv)

We address one of the crucial aspects necessary for safe and efficient operations of autonomous vehicles, namely predicting future state of traffic actors in the autonomous vehicle's surroundings. We introduce a deep learning-based approach that takes into account a current world state and produces raster images of each actor's vicinity. The rasters are then used as inputs to deep convolutional models to infer future movement of actors while also accounting for and capturing inherent uncertainty of the prediction task. Extensive experiments on real-world data strongly suggest benefits of the proposed approach. Moreover, following completion of the offline tests the system was successfully tested onboard self-driving vehicles.

Key facts. Cited by 90 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Aug 2018.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 20; 2022: 11; 2023: 28; 2024: 16; 2025: 11; 2026: 3.

90 papers.

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2022ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learningcited by 368
2022Motion Transformer with Global Intention Localization and Local Movement Refinementcited by 270
2021FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Camerascited by 239
2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
2023MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Queryingcited by 140
2021Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Priorcited by 139
2022PlanT: Explainable Planning Transformers via Object-Level Representationscited by 105
2023End-to-End Vectorized HD-map Construction with Piecewise Bezier Curvecited by 82
2021Explainability of deep vision-based autonomous driving systems: Review and challengescited by 80
2022Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantificationcited by 73
2021Learning to Predict Vehicle Trajectories with Model-based Planningcited by 63
2024ParCo: Part-Coordinating Text-to-Motion Synthesiscited by 55

38 more

2019Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safetycited by 49
2021On Exposing the Challenging Long Tail in Future Prediction of Traffic Actorscited by 48
2023ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptationcited by 41
2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 33
2021Imagining The Road Ahead: Multi-Agent Trajectory Prediction via Differentiable Simulationcited by 32
20223D Human Motion Prediction: A Surveycited by 30
2022R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinementcited by 24
2023Machine Learning for Autonomous Vehicle's Trajectory Prediction: A comprehensive survey, Challenges, and Future Research Directionscited by 23
2021Exploring Imitation Learning for Autonomous Driving with Feedback Synthesizer and Differentiable Rasterizationcited by 22
2021Efficient and Robust LiDAR-Based End-to-End Navigationcited by 22
2022CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attentioncited by 21
2024T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memorycited by 20
2021Deep Structured Reactive Planningcited by 19
2023Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embeddingcited by 19
2023SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networkscited by 18
2023RS2G: Data-Driven Scene-Graph Extraction and Embedding for Robust Autonomous Perception and Scenario Understandingcited by 17
2021Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Drivingcited by 15
2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
2023Toward Reliable Human Pose Forecasting with Uncertaintycited by 11
2024SemanticFormer: Holistic and Semantic Traffic Scene Representation for Trajectory Prediction using Knowledge Graphscited by 11
2024Planning with Adaptive World Models for Autonomous Drivingcited by 11
2023Holistic Graph-based Motion Predictioncited by 10
2021Self-Supervised Action-Space Prediction for Automated Drivingcited by 9
2023MGTR: Multi-Granular Transformer for Motion Prediction with LiDARcited by 9
2021Physically Feasible Vehicle Trajectory Predictioncited by 8
2022STrajNet: Multi-modal Hierarchical Transformer for Occupancy Flow Field Prediction in Autonomous Drivingcited by 8
2023BiFF: Bi-level Future Fusion with Polyline-based Coordinate for Interactive Trajectory Predictioncited by 8
2024OFMPNet: Deep End-to-End Model for Occupancy and Flow Prediction in Urban Environmentcited by 8
2022Context-Aware Scene Prediction Network (CASPNet)cited by 7
2023nuScenes Knowledge Graph -- A comprehensive semantic representation of traffic scenes for trajectory predictioncited by 7
2024Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Drivingcited by 7
2023PBP: Path-based Trajectory Prediction for Autonomous Drivingcited by 6
2023Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorancecited by 6
2023Semi-Supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMixcited by 6
2024Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixturecited by 6
2021Diff-Net: Image Feature Difference based High-Definition Map Change Detection for Autonomous Drivingcited by 5
2021Transformer based trajectory predictioncited by 5
2023Exploring Navigation Maps for Learning-Based Motion Predictioncited by 5

50 most cited of 90 All 90 (JSON)