Highway Entrance Congestion Scene Classification Dataset
#image classification #scene recognition #traffic monitoring #intelligent traffic systems #urban planning
- 20000 records
- 3G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-09-20
AI Analysis & Value Prop
The current transportation industry faces increasingly severe congestion problems, especially at highway entrances, where congestion greatly impacts traffic efficiency and safety. Existing traffic monitoring systems mostly rely on traditional sensors and manual monitoring, lacking intelligent analysis capabilities for complex scenes. To better address this issue, this dataset aims to provide high-quality congestion scene classification data to help improve the automation level of intelligent traffic systems. The dataset contains images of congested scenes at various highway entrances, collected using high-definition cameras under various weather conditions to ensure data diversity and representativeness. We have implemented strict quality control measures, including multiple rounds of annotation and expert review, to ensure the accuracy of annotations for each image. The images in this dataset are stored in JPG format and organized by time and scene for easy subsequent model training and testing.
Dataset Insights
Sample Examples
79925bb4**.jpg|1920*2560|443.00 KB
f7e0b7fe**.jpg|1080*1440|152.37 KB
1500e66e**.jpg|1920*2560|474.06 KB
9219934e**.jpg|2560*1920|567.41 KB
65f61b5e**.jpg|3000*4000|852.71 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| traffic_density | string | Classification of vehicle density in the image, such as low, medium, high. |
| weather_condition | string | Weather condition during image capture, such as sunny, rainy, foggy. |
| time_of_day | string | Time period during which the image was captured, such as daytime, dusk, nighttime. |
| road_condition | string | Condition of the road in the image, such as dry, slippery, snowy. |
| light_condition | string | Lighting condition in the image, such as well-lit, shadowy. |
| vehicle_type_distribution | string | Distribution of different types of vehicles in the image, such as cars, trucks, vans, motorcycles. |
| lane_usage | string | Usage status of lanes in the image, such as congested, free-flowing. |
| pedestrian_presence | string | Presence of pedestrians in the image, such as present, absent. |
| incident_presence | string | Presence of traffic incidents in the image, such as incident present, no incident. |
| construction_activity | string | Presence of construction activity in the image, such as construction present, no construction. |
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 |
Frequently Asked Questions
- What can this dataset be used for?
- The highway intersection congestion scene classification dataset can be used in intelligent transportation systems to enhance the ability to automatically recognize traffic congestion situations.
- What kind of images are included in the dataset?
- The dataset includes images of various congestion scenes at highway intersections.
- Why is highway intersection congestion scene classification important?
- Highway intersection congestion scene classification aids in traffic management, enhancing road utilization efficiency and reducing congestion.
- Which industries or fields is this dataset suitable for?
- This dataset is suitable for the transportation industry, especially in areas where there is a need to enhance intelligent transportation system recognition capabilities.
- How can this dataset be used to improve intelligent transportation systems?
- By training models within intelligent transportation systems to recognize and classify congestion scenes at highway intersections, thereby enhancing the system's ability to respond to traffic conditions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Highway Entrance Congestion Scene Classification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/4000b230a23a9decc619a01bd779809a},
urldate={2025-09-15},
keywords={highway entrance, congestion scenes, image classification dataset, traffic monitoring},
version={1.0}
}Using this in research? Please cite us.
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