DeepAccident: A Motion and Accident Prediction Benchmark for V2X Autonomous Driving
On the map: End-to-end autonomous driving → Adversarial scenarios and safety testing
Abstract (arXiv)
Safety is the primary priority of autonomous driving. Nevertheless, no published dataset currently supports the direct and explainable safety evaluation for autonomous driving. In this work, we propose DeepAccident, a large-scale dataset generated via a realistic simulator containing diverse accident scenarios that frequently occur in real-world driving. The proposed DeepAccident dataset includes 57K annotated frames and 285K annotated samples, approximately 7 times more than the large-scale nuScenes dataset with 40k annotated samples. In addition, we propose a new task, end-to-end motion and accident prediction, which can be used to directly evaluate the accident prediction ability for different autonomous driving algorithms. Furthermore, for each scenario, we set four vehicles along with one infrastructure to record data, thus providing diverse viewpoints for accident scenarios and enabling V2X (vehicle-to-everything) research on perception and prediction tasks. Finally, we present a baseline V2X model named V2XFormer that demonstrates superior performance for motion and accident prediction and 3D object detection compared to the single-vehicle model.
Key facts. Cited by 73 papers in the map (data through 7 Oct 2026). Placed in Adversarial scenarios and safety testing, one of 9 directions in End-to-end autonomous driving. Builds on 20 of its 25 references that are in the map. First posted on arXiv 3 Apr 2023.
Builds on
20 of 25 references.
Closest ancestors · 1
Same direction, newest first
Other references · 19
- 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
- 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
- 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
- 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
- 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
- 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 890
- 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 711
- 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
- 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
- 2022DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectioncited by 270
- 2021FIERY: Future Instance Prediction in Bird's-Eye View from Surround Monocular Camerascited by 239
- 2022CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformerscited by 227
7 more
- 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
- 2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
- 2022V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Drivingcited by 157
- 2021AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehiclescited by 132
- 2023Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baselinecited by 40
- 2022TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillancecited by 20
- 2018VIENA2: A Driving Anticipation Datasetcited by 19
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Citing papers per year: 2023: 5; 2024: 21; 2025: 26; 2026: 21.
73 papers.
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- 2025VRU-Accident: A Vision-Language Benchmark for Video Question Answering and Dense Captioning for Accident Scene Understandingcited by 20
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- 2024Pre-Trained Vision Models as Perception Backbones for Safety Filters in Autonomous Driving29 Oct 2024
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- 2025Investigating Traffic Accident Detection Using Multimodal Large Language Models23 Sep 2025
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- 2023Towards Vehicle-to-everything Autonomous Driving: A Survey on Collaborative Perceptioncited by 38
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- 2023Vision-Based Traffic Accident Detection and Anticipation: A Surveycited by 31
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- 2026CURVE: Learning Causality-Inspired Invariant Representations for Robust Scene Understanding via Uncertainty-Guided Regularization28 Jan 2026
- 2026Towards Efficient 3D Object Detection for Vehicle-Infrastructure Collaboration via Risk-Intent Selection6 Jan 2026
- 2025SAVeD: A First-Person Social Media Video Dataset for ADAS-equipped vehicle Near-Miss and Crash Event Analyses19 Dec 2025
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