Mobiusi/Road-Blockage-and-Illegal-Parking-Identification-Dataset

Road Blockage and Illegal Parking Identification Dataset

The current traffic industry faces increasingly severe issues of road blockages and illegal parking, affecting the smoothness and safety of urban traffic. Existing traffic monitoring systems often rely on manual inspections, which are inefficient and prone to omissions. This dataset aims to provide high-quality object detection data for smart traffic systems to automatically identify road blockages and illegal parking situations, thereby enhancing real-time monitoring capabilities. During the construction of the dataset, high-resolution cameras were used to shoot around the clock at major urban traffic intersections, and machine learning algorithms were employed for automatic annotation, ensuring data diversity and accuracy. Strict quality control measures were implemented, including expert reviews and multiple rounds of annotation, to ensure high quality and consistency of the data. The data is stored in JPEG format and organized according to image IDs for easy subsequent data processing and analysis.

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
blockage_type	string	Describes the type of blockage identified in the image, such as traffic jam or illegal parking.
vehicle_count	int	Total number of vehicles identified in the image.
road_segment	string	Specifies the specific road segment or location where blockage or illegal parking is identified.
obstruction_severity	string	Grades the severity of the road blockage situation, such as minor, moderate, or severe.
weather_conditions	string	Weather conditions at the time the image was captured, potentially including sunny, cloudy, or rainy.
daytime	string	The time of day when the image was captured, such as morning, afternoon, or evening.
pedestrian_count	int	Number of pedestrians identified in the image.
parking_signs_present	boolean	Indicates whether parking signs are present in the image.

Compliance Statement

Authorization Type	CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com