Tunnel Vehicle Collision Damage Segmentation Dataset

#semantic segmentation #object detection #traffic monitoring #accident analysis #safety evaluation
  • 5000 records
  • 1.2G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-11

AI Analysis & Value Prop

The current transportation industry is facing increasingly serious traffic safety issues, especially in special environments like tunnels where vehicle collision accidents occur frequently, posing significant challenges to traffic management and driving safety. Existing monitoring systems have insufficient real-time detection and analysis capabilities for accidents, which cannot quickly and effectively provide detailed information about the accident scene, leading to difficulties in subsequent handling and evaluation. This dataset aims to assist researchers and engineers in developing more precise intelligent monitoring and accident analysis systems by providing high-quality tunnel vehicle collision damage segmentation data. Data collection is conducted using high-resolution cameras in multiple tunnel environments to ensure coverage of various traffic and weather conditions. To ensure data quality, we implemented multiple rounds of labeling and consistency checks, with expert review to ensure the accuracy of the labels. The data is stored in JPG format, with a clear file structure, facilitating subsequent processing and analysis.

Dataset Insights

Sample Examples

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Technical Specifications

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

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Cite this Work

@dataset{Mobiusiundefined,
  title={},
  author={Mobiusi},
  year={undefined},
  url={https://www.mobiusi.com/datasets/283c4aad7ea4c49833181ac77b304704?dataset_scene_id=1},
  urldate={},
  keywords={},
  version={}
}

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