Highway Severe Accident Detection Dataset
#Object detection #image classification #Traffic safety #accident detection #intelligent driving
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-05-03
AI Analysis & Value Prop
In the current transportation industry, frequent traffic accidents lead to significant economic losses and casualties, especially on highways where the speed of accident detection and response is crucial. However, existing accident detection systems commonly rely on manual monitoring, which is inefficient and prone to missed reports. To address this issue, we have constructed the Highway Severe Accident Detection Dataset to provide high-quality training data for intelligent transportation systems, improving the accuracy and timeliness of automatic detection technology. This dataset is collected using high-resolution cameras on highways and includes images before and after accidents, ensuring diversity and authenticity. We have employed multi-round annotations and expert reviews to ensure high annotation accuracy. A total of 5000 images have been collected, stored in JPG format, with a file size of approximately 1.2G, organized so that each image has a corresponding metadata file for easy subsequent processing and analysis.
Dataset Insights
Sample Examples
a39922f6**.jpg|1920*2560|443.00 KB
06ae5980**.jpg|3000*4000|852.71 KB
72c14b1a**.jpg|1080*2400|179.79 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| vehicle_count | int | The number of vehicles involved in the accident in the image. |
| accident_severity | string | The classification of the severity of the accident, such as minor, moderate, or severe. |
| weather_condition | string | The weather conditions at the time the image was taken, e.g., sunny, rainy, foggy. |
| road_condition | string | The condition of the road at the accident scene, such as dry, slippery, or icy. |
| visibility_level | string | The level of visibility in the image, such as clear, moderate, or poor. |
| light_condition | string | The lighting condition at the time of capturing, e.g., daytime, nighttime, twilight. |
| lane_count | int | The number of lanes at the location of the accident. |
| injury_presence | boolean | Indicates whether there are signs of injuries to individuals in the image. |
| emergency_services_presence | boolean | Indicates the presence of emergency services vehicles, such as ambulances or police cars, in the image. |
| time_of_day | string | The time of day when the image was captured, such as morning, afternoon, or night. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| 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 is the Highway Severe Accident Detection Dataset?
- The Highway Severe Accident Detection Dataset is an image dataset focused on recognizing and detecting severe traffic accidents on highways, aimed at supporting the development and optimization of intelligent transportation systems.
- What does this dataset contain?
- The dataset primarily contains highway accident images, which are used to train and validate computer vision models for automated accident detection.
- How to use the Highway Severe Accident Detection Dataset for object detection?
- The images in the Highway Severe Accident Detection Dataset can be used to train machine learning algorithms, particularly object detection models, to enhance the capability of identifying and analyzing accident scenes.
- Why is the Highway Accident Detection Dataset important for intelligent transportation systems?
- This dataset can help improve the automation and accuracy of accident detection, thereby enhancing traffic flow management and accident response speed, which is crucial for the development of intelligent transportation systems.
- What machine learning tasks is this dataset suitable for?
- This dataset is suitable for object detection, computer vision, and image analysis-related machine learning tasks, particularly in applications within the traffic industry.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Highway Severe Accident Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/cef53541bf2f7352a3b22572e5d222cd},
urldate={2025-09-15},
keywords={Highway dataset, traffic accident detection, object detection dataset, intelligent transportation},
version={1.0}
}Using this in research? Please cite us.
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