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Driver Behaviour Dataset

Driver Behaviour Dataset provides RGB and infrared images of 304 drivers with detailed annotations on dangerous driving, fatigue behavior, and visual movement behavior, supporting research in behavior monitoring, monitoring driver performance, fleet safety, road safety, and the development of AI models for analyzing risky driving and drivers behavior to achieve improved safety and safer driving practices for fleet management and traffic safety.

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  • people
    304
  • images
    2 400+
  • Auto
  • Computer Vision
  • Machine learning
  • Security

Driver Behaviour Dataset provides RGB and infrared images of 304 drivers with detailed annotations on dangerous driving, fatigue behavior, and visual movement behavior, supporting research in behavior monitoring, monitoring driver performance, fleet safety, road safety, and the development of AI models for analyzing risky driving and drivers behavior to achieve improved safety and safer driving practices for fleet management and traffic safety.

Get in touch Download sample
  • Auto
  • Computer Vision
  • Machine learning
  • Security
  • people
    304
  • images
    2 400+

Dataset Info

Characteristic Data
Description Images of driver recorded with RGB and infrared cameras
Data types Image
Tasks Detection, Driver behavior analysis
Total number of people 304
Total number of images 2 432
Type of behaviour Dangerous behavior, Fatigue behavior, Visual movement behavior
Labeling Metadata(nationality, gender, age, collection time and etc)
Gender Male, Female
Ethnicity Indians, Caucasian, African
Age young adults, middle-aged, elderly
Collection time day, evening and night
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Statistics

Distribution by gender
Distribution by ethnicity
Distribution by age

Technical
Characteristics

Characteristic Data
Image extension jpg
Image resolution 640x480
Device binocular camera of RGB and infrared channels
Accuracy of each person's action is more than 95%
Source and collection methodology. Data was collected by a partner of Unidata.

Dataset Use Cases

  • Automotive Safety & Research

    Enhancing Road Safety Through Driver Monitoring

    Driver Behaviour Dataset provides insights into driving behaviors such as distracted driving, aggressive driving, and unsafe practices. Researchers and engineers use it to design safety solutions that help reduce traffic accidents. By analyzing data, this driver dataset supports studies on road safety and effective risk management.

  • Fleet Management

    Improving Fleet Safety and Performance

    Fleet managers rely on such datasets to identify risky behaviors and improve driver performance. The dataset supports behaviour monitoring and helps reduce unsafe driving in large fleets. With detailed data, management systems encourage safer driving practices, leading to improved fleet safety, reduced costs, and lower accident risks.

  • Insurance & Risk Assessment

    Detecting Risky Driving for Better Risk Models

    Insurance providers use driver behavior datasets to analyze driving habits and identify unsafe behaviors like speeding, tailgating, or distracted driving. This information helps build accurate risk models and monitoring systems. By spotting risky driving, insurers can offer personalized plans, encourage safer driving, and improve traffic safety outcomes.

  • Driver Training & Coaching

    Coaching Drivers to Improve Performance

    This dataset supports driver coaching by highlighting patterns of risky driving and unsafe behaviors. Training programs can use this data to show drivers where improvements are needed. With clear insights, coaching systems help drivers adopt safer driving habits, improving driver performance and reducing the likelihood of traffic accidents.

FAQs

What does Driver Behaviour Dataset include?
It contains 2,432 images of drivers representing 304 individuals. It includes three main driving behaviors: dangerous actions, fatigue behavior, and visual movement patterns. All samples come with metadata such as nationality, gender, age, and collection time.
How was the dataset collected?
The dataset was recorded using binocular RGB and infrared cameras, capturing driver behaviours in different lighting conditions, including day, evening, and night. Each person’s action is annotated with an accuracy of over 95%, ensuring high-quality behaviour monitoring data.
What format is the dataset provided in?
All images are delivered in JPG format with a resolution of 640x480. Annotations and metadata are included for easy integration into management systems, machine learning frameworks, and behaviour monitoring solutions.
Can I request a sample of the dataset before purchase?
Yes, a sample of the driver dataset can be requested. This lets you evaluate the image quality, annotation accuracy, and labeling structure to ensure the data supports your behaviour monitoring or driver performance research.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All Unidata datasets, including Driver Behaviour Dataset, fully comply with GDPR and relevant data protection laws. The data is gathered from lawful sources and anonymized to ensure ethical use while enabling behavior monitoring, fleet management, and traffic safety analysis.
How are Unidata datasets stored?
Unidata securely stores all datasets on AWS cloud infrastructure, ensuring both high availability and scalability. The storage process follows ISO 27001 and ISO 27701 standards, providing a privacy-focused and reliable environment for driver behavior data used in fleet safety and risk management systems.
How long does it take to receive the dataset?
After submitting a request, our team will review your details and handle all necessary documentation. Once payment and signing are complete, Driver Behaviour Dataset will be delivered within 3–10 days, allowing quick access to images for analyzing driver behaviors and developing monitoring solutions.
Is this a real-world dataset or synthetic data?
This is a real-world dataset collected via binocular RGB and infrared cameras by a Unidata partner. The dataset captures authentic driving behaviors such as aggressive driving and fatigue patterns, making it ideal for driver performance analysis, safety improvement research, and behavior monitoring applications.
Still have questions about using Unidata datasets? Read our user-guides

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