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Exterior driving dataset: Greater Los Angeles

Updated May 7, 2025

ADAS and AV training data with 82 hours of footage at 10 frames per second collected using a synchronized multi-camera setup. This dataset captures up to 5,500 kilometers of highways, urban and rural environments, with both day and night coverage and zero route repetition.

Specifications

Location
Los Angeles, CA
Modality
2D Images
Distance covered (kms)
5500
Sensor setup
3x camera 1 (120 deg FoV) - 1x camera 2 (65 deg FoV)
Vehicle type
Sedan
Data volume
82 hours of recording @10 FPS
Year of collection
2024
Time of day
Day & Night
Environment distribution distribution
Highways: 70% - Urban: 20% - Rural: 10%
Licensable
Yes
Special features
No route repetition

Accelerate model development & training processes

  • Contextual driving intelligence

    Enable your AI models to navigate and respond to real-world traffic conditions, infrastructure variations and critical driving events with enhanced accuracy.

  • Scene perception and understanding

    Train AI models to accurately perceive, classify and understand complex road environments including pedestrians, vehicles, signage, and changing weather or lighting conditions.

  • Anomaly and edge case detection

    Detect rare or abnormal scenarios to strengthen system resilience, improve safety and reduce failure rates.

  • Scenario-rich training for on-road reliability

    Expose AI systems to a wide spectrum of urban, rural and highway driving environments to ensure generalized performance across geographies and driving styles.

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Case Study

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  • Curating high-quality data for the training and validation of ADAS and AV models

    An autonomous vehicle shown driving on a busy highway.

    Discover how TELUS Digital used our proven field operations testing (FOT) experience to create a high-quality dataset for training advanced driver assistance systems (ADAS) and autonomous vehicles (AV).


    • 12TBdata captured daily


    • 7500kmapproximate total distance covered

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