Traffic Congestion Dataset in Adverse Weather
#Target detection #object recognition #Traffic management #intelligent transportation #urban planning
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
The current traffic industry faces challenges including the impact of weather changes on traffic flow. Under adverse weather conditions, traffic congestion becomes more pronounced. Existing traffic management systems often lack specific data support for traffic conditions under different weather scenarios, leading to less precise decision-making. This dataset aims to provide a rich collection of traffic congestion images in adverse weather, assisting researchers and developers in enhancing the intelligence level of traffic management. Data collection is carried out using high-resolution cameras at major city junctions around the clock, ensuring coverage of various weather conditions. Quality control involves multiple rounds of annotation and expert review mechanisms to ensure consistency and accuracy of annotations. The data storage format is JPEG, organized by folder classification, with each folder corresponding to a weather condition.
Dataset Insights
Sample Examples
01d98a9b**.jpg|5824*4368|1.18 MB
bae32411**.jpg|5824*4368|1.14 MB
41a3845d**.jpg|3024*4032|1.03 MB
dd3186c8**.jpg|5824*4368|1.24 MB
2a875992**.jpg|5824*4368|1.15 MB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| weather_condition | string | Indicates the weather condition at the time the picture was taken, such as rainy, snowy, foggy, etc. |
| traffic_density | integer | Indicates the level of traffic density in the image, commonly represented by numbers. |
| number_of_vehicles | integer | Indicates the total number of vehicles appearing in the image. |
| vehicle_types | string | Represents different types of vehicles appearing in the image, such as cars, trucks, buses, etc. |
| road_condition | string | Indicates the road condition in the image, such as slippery, icy, or flooded. |
| visibility_level | integer | Indicates the level of visibility in the image, commonly represented by numbers. |
| time_of_day | string | Indicates the time of day when the picture was taken, such as morning, noon, evening, etc. |
| emergency_vehicles_present | boolean | Indicates whether there are emergency vehicles present in the image, such as police cars, ambulances, etc. |
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 machine learning tasks can this dataset be used for?
- This dataset is primarily used for object detection tasks, helping to identify and analyze traffic congestion under severe weather conditions.
- How can this dataset be applied in traffic management?
- Traffic management departments can use this dataset to train models for predicting and handling traffic congestion under severe weather conditions, improving the efficiency of traffic flow management.
- What severe weather conditions are included in the images of this dataset?
- The dataset includes images under various severe weather conditions, such as rain, snow, and heavy fog, depicting actual traffic congestion scenarios.
- What traffic problems can be improved using this dataset?
- By analyzing traffic data under severe weather conditions, traffic congestion can be more accurately predicted, thus improving traffic flow and reducing accidents.
- Can this dataset be used for autonomous driving research?
- Yes, autonomous driving research can utilize this dataset to train and test their systems' performance in severe weather conditions, enhancing the system's safety and reliability.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Traffic Congestion Dataset in Adverse Weather},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/11265d34c9cbea9249c7dc975a4a9b15?dataset_scene_id=1},
urldate={2025-09-15},
keywords={Traffic congestion dataset, adverse weather traffic, target detection dataset, traffic management, intelligent transportation},
version={1.0}
}Using this in research? Please cite us.
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