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file_name
stringclasses
5 values
quality
stringclasses
5 values
vehicle_count
stringclasses
5 values
congestion_level
stringclasses
3 values
weather_conditions
stringclasses
3 values
road_condition
stringclasses
2 values
time_of_day
stringclasses
2 values
traffic_signal_status
stringclasses
5 values
lane_count
stringclasses
3 values
incident_presence
stringclasses
5 values
143594de27b658c015be8fac2e82dfbe.jpg
1080*1440
8
Severe
Clear
Dry
Daytime
Unclear
3
Traffic incident present
79262177896f06027f74c44cbcd6c473.jpg
1920*2560
5
Moderate
Clear
Dry
Daytime
None
2
Traffic accident present
8943fa5423ce7d64ec04d39567f186d1.jpg
3000*4000
at least 3 vehicles
severe
clear
dry
daytime
not displayed
at least 2 lanes
traffic incident present
bc1dac27064a27dfeb871a02754f0c6a.jpg
2560*1920
20
Severe
Sunny
Dry
Daytime
Red light
3
None
c8053dfb9d88f3e9a6b3cee2dc552149.jpg
1920*1080
6
Moderate
Sunny
Dry
Daytime
No signal light
2
Yes

Highway Traffic Congestion Recognition Dataset

The current transportation industry faces serious traffic congestion issues, leading to time wastage and environmental pollution. Existing traffic monitoring systems often rely on traditional manual inspections, which are inefficient and prone to errors. This dataset aims to provide high-quality traffic congestion image data to support deep learning-based object detection technologies, improving the automation and accuracy of traffic condition recognition. The dataset includes traffic images from various highways, with collection devices including HD cameras and the collection environment being actual highways. To ensure data quality, multi-round annotation and expert review are used to ensure consistency and accuracy of each image and label. The data is stored in JPEG format, organized with each image corresponding to an ID, file path, and annotation information.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
vehicle_count int The total number of vehicles appearing in the image.
congestion_level string The level of traffic congestion depicted in the image, such as severe, moderate, or mild.
weather_conditions string The weather conditions at the time the image was captured, such as sunny, cloudy, or rainy.
road_condition string The road conditions depicted in the image, such as dry, slippery, or snowy.
time_of_day string The time period when the image was captured, such as day, night, or dusk.
traffic_signal_status string The status of the traffic signal at the time of capture, such as red, green, or yellow.
lane_count int The number of visible lanes in the image.
incident_presence boolean Indicates whether a traffic incident is 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

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