Mobiusi/Highway-Severe-Accident-Detection-Dataset

Highway Severe Accident Detection Dataset

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.

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	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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com