Traffic Congestion Recognition Dataset
#object detection #image classification #traffic management #smart traffic systems #urban planning
- 50000 records
- 3.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-03-11
AI Analysis & Value Prop
The main challenge currently faced by the transportation industry is the increasingly severe urban congestion problem, leading to low traffic efficiency and aggravated environmental pollution. Existing traffic monitoring systems often rely on static data, lacking real-time performance and flexibility. To solve this problem, this dataset aims to provide high-quality congestion recognition data to support real-time decision-making and management of intelligent traffic systems. The dataset includes traffic images collected from different cities and time periods, annotated with congestion levels of various areas. Data collection is conducted using high-definition cameras during peak traffic periods to ensure coverage of various traffic situations. Multi-round annotation and expert review quality control measures are used to ensure consistency and accuracy of the data. The data is stored in JPEG format, organized by time and location for easy analysis and use.
Dataset Insights
Sample Examples
bb41a384**.jpg|1920*2560|837.88 KB
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| vehicle_count | int | The total number of vehicles detected in the image. |
| traffic_density | float | The density of vehicles in the image, indicating the level of traffic congestion. |
| road_occupancy | float | The proportion of the road occupied by detected vehicles. |
| weather_condition | string | The weather conditions depicted in the image, such as sunny or rainy. |
| time_of_day | string | The time of day when the image was captured, such as morning, afternoon, or evening. |
| traffic_signal_state | string | The state of the traffic lights in the image, such as red or green. |
| road_type | string | The type of road depicted in the image, such as a highway or urban road. |
| congestion_level | string | The level of congestion assessed based on the number of vehicles and traffic density, such as low, medium, or high. |
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 |
Frequently Asked Questions
- What is the Road Congestion Detection Dataset?
- The Road Congestion Detection Dataset is an object detection dataset focused on detecting traffic congestion through images, helping intelligent traffic management systems identify and analyze road congestion situations.
- Which industries is the Road Congestion Detection Dataset suitable for?
- The Road Congestion Detection Dataset is suitable for the transportation industry, particularly playing a significant role in the development and optimization of intelligent traffic systems.
- What are the benefits of using the Road Congestion Detection Dataset?
- Using the Road Congestion Detection Dataset can enhance the efficiency of traffic management systems by accurately detecting and analyzing traffic congestion situations, optimizing traffic flow, and reducing the frequency of congestion occurrences.
- What is the data format of the Road Congestion Detection Dataset?
- The data format of the Road Congestion Detection Dataset primarily consists of images, which are used for detecting and analyzing congestion situations on roads.
- How can the Road Congestion Detection Dataset be applied in traffic systems?
- The Road Congestion Detection Dataset can be applied in traffic systems by training object detection models to identify traffic congestion, thus providing data support for traffic signal control and route planning.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Traffic Congestion Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d688b6e663549f2ef152e6b49d65e935},
urldate={2025-09-15},
keywords={traffic congestion recognition, traffic dataset, object detection dataset, smart traffic system},
version={1.0}
}Using this in research? Please cite us.
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