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Home/Cabin Driver Behavior and State Perception for Safe Driving Monitoring Dataset

Cabin Driver Behavior and State Perception for Safe Driving Monitoring Dataset

#driver state classification #behavior recognition #object detection #image classification #in-cabin visual perception #driver distraction alerts #fatigue monitoring #intelligent cabin safety #in-vehicle monitoring #driving behavior analysis

22584
1.2GB
piece
CATL
MOBIUSI INC

Updated:2026-11-05

AI Analysis & Value Prop

This dataset contains in-cabin images for perceiving driver behavior and state, along with image identifiers, image paths, annotation file paths, class IDs, image dimensions, and image formats. It supports research and development in driver-state recognition and safe-driving monitoring, including the training and evaluation of in-cabin vision models. Typical applications include detecting driver distraction or abnormal states, developing driver monitoring systems, and validating intelligent-cabin safety features.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
image_id	string	A unique identifier for the image record.
image_path	string	The file path or location of the image.
label_path	string	The file path or location of the annotation associated with the image.
category_id	array	The identifier for the image's assigned class.
image_width	number	The width of the image in pixels.
image_format	string	The image file format.
image_height	number	The height of the image in pixels.

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 does the dataset contain?: It contains in-cabin images related to drivers, together with fields for image identifiers, image and annotation file paths, class IDs, image dimensions, and image formats. These fields help link images with annotations and basic image specifications.

Are the total sample count and image resolution specified?: The available information does not specify the total number of samples or a defined resolution range. Width, height, and image format fields are provided so these specifications can be checked for individual images after access.

How can I access and use the dataset?: Obtain the images and corresponding annotation files through the dataset listing or from the data provider. Use the image paths, annotation file paths, and class IDs to load and organize the data. Available file formats and delivery methods depend on the provider's release details.

What are the dataset licensing terms?: Specific licensing terms are not included in the available information. Before use, consult the dataset listing or contact the provider to confirm permitted use, commercial-use rights, and applicable privacy and compliance requirements.

Which model development tasks does it support?: The data can support training and evaluation for driver-state classification, behavior recognition, and related in-cabin vision tasks. It may also assist in developing fatigue or distraction monitoring, safe-driving alerts, and intelligent-cabin monitoring features. Results depend on the class definitions, annotation quality, and data coverage.

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Cite this Work

@dataset{Mobiusi2026,
  title={Cabin Driver Behavior and State Perception for Safe Driving Monitoring Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/2241d1dde9805f00b1c6ac5776596bd6},
  urldate={2026-11-05},
  keywords={driver behavior dataset,in-cabin monitoring data,driver state recognition,fatigue driving detection,distracted driving recognition,safe driving monitoring,intelligent cabin vision,driving behavior recognition},
  version={1.0}
}

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