Rainy Traffic Accident Detection Dataset
#object detection #image recognition #traffic monitoring #safety analysis #accident prevention
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-01-06
AI Analysis & Value Prop
The main challenge currently facing the transportation industry is the high frequency of accidents under rainy conditions, which increases traffic safety risks. Existing monitoring systems lack accuracy and real-time performance in rainy weather, making it difficult to effectively identify and warn of potential traffic accidents. This dataset aims to assist researchers in developing more accurate object detection models by providing high-quality images of rainy traffic accidents and their annotations. Data is collected using high-resolution cameras positioned at typical urban traffic intersections, monitoring rainy traffic conditions around the clock. To ensure data quality, we have implemented multiple rounds of annotation, expert reviews, and consistency checks, ensuring that each image's annotation accuracy is above 95%. Data is stored in JPG format and organized by date and location, facilitating subsequent analysis and research.
Dataset Insights
Sample Examples
0316742e**.jpg|1927*2558|321.39 KB
6f65575e**.jpg|3024*4032|780.09 KB
5382ec70**.jpg|3072*4080|1.06 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| weather_conditions | string | The type of weather depicted in the image, such as light rain or heavy rain. |
| vehicle_count | int | The total number of vehicles appearing in the image. |
| accident_presence | boolean | Whether there is a traffic accident present in the image. |
| road_type | string | The type of road depicted in the image, such as highway or urban road. |
| lighting_conditions | string | The lighting conditions depicted in the image, such as daytime or nighttime. |
| pedestrian_presence | boolean | Whether there are pedestrians appearing in the image. |
| traffic_signs_present | boolean | Whether traffic signs are visible in the image. |
| hazardous_conditions | string | Description of hazardous conditions in the image that might lead to accidents. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What types of images are included in the rainy traffic accident detection dataset?
- The dataset focuses on traffic accidents during rainy conditions and includes numerous images of traffic accident scenes captured in the rain.
- What are the industrial applications of using the rainy traffic accident detection dataset?
- The dataset can be used to help develop and test accident detection algorithms for autonomous vehicles in rainy environments, enhancing traffic safety.
- How does the object detection in the rainy traffic accident dataset differ from regular datasets?
- The rainy traffic accident detection dataset focuses on object detection under rainy conditions, presenting higher challenges such as dealing with low light and rain interference.
- How can the rainy traffic accident detection dataset be effectively used for model training?
- When training models, data augmentation techniques can be employed to simulate various rainy conditions, thereby enhancing the model's robustness in real-world applications.
- What value does the rainy traffic accident detection dataset provide to intelligent transportation systems?
- This dataset can help intelligent transportation systems more accurately identify and warn about traffic accidents, especially under adverse weather conditions, enhancing the system's prevention and response capabilities.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Rainy Traffic Accident Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/70c740f7969218b5acaaa68bb81a81e9},
urldate={2025-09-15},
keywords={rainy traffic dataset, traffic accident detection, object detection dataset},
version={1.0}
}Using this in research? Please cite us.
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