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Dynamic Road Participant Image Dataset
Synthetic Images & Vision Datasets
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£8,000
About
Description:
This dataset provides a diverse collection of dynamic road participant images, generated using high-fidelity synthetic simulation environments. It covers moving vehicles, pedestrians, and parked vehicles with protective covers that cause partial occlusion. Each target type is modeled with realistic dimensions, motion states, and environmental integration to accurately reflect real-world traffic scenes.
The dataset is designed for dynamic obstacle detection tasks in autonomous driving, Advanced Driver Assistance Systems (ADAS), and Driver Monitoring Systems (DMS). It supports model training for identifying and tracking multiple classes of road participants in varied operational contexts, enhancing perception accuracy and safety decision-making.
All samples are annotated with object detection bounding boxes in JSON or COCO-compatible formats. Label categories include vehicles (with and without occlusion), pedestrians, bicycles, and other dynamic traffic participants. The annotations provide precise spatial localization for each object instance, ensuring balanced class representation for robust detection performance.
The synthetic generation process incorporates controlled variation in traffic density, lighting conditions (daytime, nighttime, low-light), weather scenarios, and occlusion states. Data was generated from a simulated moving vehicle perspective, replicating both urban and suburban road environments, intersections, and mixed traffic conditions.
By combining photorealistic rendering, human annotation, and diverse environmental simulation, this dataset supports the development of high-accuracy dynamic obstacle detection models, improves tracking performance, and enhances overall road scene understanding in intelligent transportation systems.
Keywords: dynamic obstacle detection road participant vehicle pedestrian bicycle occlusion recognition traffic
Sector: Intelligent Transportation / Autonomous Driving / ADAS / DMS
Metrics: Object detection accuracy, tracking recall rate
Entities: Vehicles, pedestrians, bicycles, dynamic road participants
Geographies: China (urban and suburban road environments)
Price Range (USD): 4000–20000
Source type: Synthetic data generation from simulation environment, human annotation
Resolution: 1920×1080
Total Images: Over 20,000 images with diverse traffic and environmental conditions
Unique Scenes: Multiple road layouts with varied traffic density, lighting, and occlusion states
Annotation Format: JSON / COCO-compatible
Annotation Type: Object detection bounding boxes
Sample Images:
Additional Notes
Usage Notes & Services
©️ Copyright & Licensing
- All rights, title, and copyright for this dataset are the exclusive property of Join Intelligence (JoinAI).
- This dataset is provided under a proprietary license. Without our express written permission, any form of redistribution, modification, public display, or commercial resale is strictly prohibited. 📜 Ethics & Compliance
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- The use of this dataset for any illegal purpose is strictly prohibited. Users are solely responsible for any and all legal consequences resulting from its misuse. 🚀 Our Service Advantages
- Actively Maintained: The dataset is still expanding and being updated regularly. For the most up-to-date version, please contact us directly.
- Full-Spectrum Customization: We offer comprehensive data customization services. This includes adjusting image formats and annotation specifications, as well as creating entirely new datasets from scratch—from collection to annotation—to meet your unique project requirements.
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