Hub Station Underground Parking Lot Abnormal Gathering and Traffic Congestion Event Dataset
#Event Detection #Behavior Analysis #Traffic Monitoring #Parking Lot Management #Abnormal Detection
- Records
- 500 records
- Size
- 1.2G
- Format
- MP4/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
The current transportation industry faces increasingly severe issues of parking lot congestion and abnormal gatherings, especially at large hub stations. Delays due to queuing, payment, and charging often lead to prolonged congestion and gathering of people, affecting overall traffic efficiency. Existing monitoring methods largely rely on manual observation, lacking systematic data support to reflect parking lot usage in real-time and accurately. This dataset aims to automatically capture and record abnormal events through video surveillance technology to provide data support for traffic management. Data collection is conducted using high-resolution surveillance cameras, capturing footage under different time periods and weather conditions to ensure coverage of various scenarios. In terms of quality control, multiple rounds of annotation and consistency checks were implemented, and expert reviews were conducted to enhance data accuracy. Finally, the data is stored in MP4 format for easy subsequent analysis and processing.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| duration | string | Duration |
| quality | string | Resolution |
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 Hub Station Underground Parking Lot Anomaly Aggregation and Traffic Blockage Event Dataset?
- This dataset includes video data monitoring long-term blockages or crowd gatherings in underground garages due to queuing, payment, charging, etc.
- What is the primary application domain of this dataset?
- This dataset is primarily used in the transportation sector to analyze and understand congestion and anomalous gatherings in underground parking lots.
- What modality of information does the Hub Station Underground Parking Lot Anomaly and Traffic Blockage Event Dataset contain?
- The dataset mainly contains video information to monitor the conditions within underground garages.
- How can this dataset help improve traffic management?
- By analyzing the recorded congestion and gathering events in the videos, managers can devise effective measures to improve traffic flow and safety in underground parking lots.
- What specific issues can be studied using this dataset?
- Researchers can use this dataset to analyze causes of congestion, crowd gathering patterns, and develop corresponding mitigation measures.
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Cite this Work
@dataset{Mobiusi2025,
title={Hub Station Underground Parking Lot Abnormal Gathering and Traffic Congestion Event Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/5ecf0b212212776f183be6fafc201c3e?cate=4},
urldate={2025-09-15},
keywords={Traffic Monitoring Dataset, Parking Lot Abnormal Events, Video Dataset, Event Detection},
version={1.0}
}Using this in research? Please cite us.
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