Tunnel Vehicle Collision Damage Segmentation Dataset

#semantic segmentation #object detection #traffic monitoring #accident analysis #safety evaluation
Records
5000 records
Size
1.2G
Format
JPG/PNG/JSON
Provider
MOBIUSI INCMOBIUSI INC
Updated
v1.02026-11-04
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.

Overview

Dataset Insights

Preview

Sample Examples

2dbb87a5**.jpg|1920*2560|245.03 KB

6937c139**.jpg|2560*1920|460.51 KB

7d05086c**.jpg|4368*5824|563.85 KB

a2142c11**.jpg|2560*1920|259.65 KB

Schema

Technical Specifications

file_namestringFile name
qualitystringResolution
vehicle_typestringIdentifies the type of vehicle in the image.
damage_typestringIdentifies the type of damage on the vehicle in the image.
damage_severitystringAssesses the severity of collision damage on the vehicle.
tunnel_structurestringIdentifies the type of tunnel structure in the image.
lighting_conditionsstringDescribes the lighting conditions at the time the image was taken.
traffic_densitystringAssesses the traffic density shown in the image.
damage_locationstringMarks the precise location of damage on the vehicle.

Trust

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

FAQ

Frequently Asked Questions

What is the primary purpose of this dataset?
The main purpose of the Tunnel Vehicle Collision Damage Segmentation Dataset is to improve the efficiency and accuracy of damage identification in traffic accident analysis.
What modality does this dataset belong to?
This dataset belongs to the image modality.
In which industry sector is this dataset mostly used?
This dataset is primarily used in the transportation industry.
What problems can this dataset help solve?
The dataset can assist in enhancing damage detection and analysis capabilities in collision accidents.
Why is the tunnel environment chosen as the scene for data collection?
The tunnel environment presents unique lighting conditions and spatial constraints, which can enhance model prediction capabilities under complex conditions.

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Cite this Work

@dataset{Mobiusi2025,
  title={Tunnel Vehicle Collision Damage Segmentation Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/283c4aad7ea4c49833181ac77b304704?dataset_scene_id=1},
  urldate={2025-09-15},
  keywords={tunnel vehicles, collision damage, semantic segmentation, traffic safety dataset},
  version={1.0}
}

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