Highway Nighttime Traffic Congestion Recognition Dataset
#target detection #image recognition #traffic management #intelligent transportation #urban planning
- 5000 records
- 3.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
AI Analysis & Value Prop
The current transportation industry is facing increasingly severe nighttime traffic congestion issues, especially in urban center areas, leading to low traffic efficiency and safety hazards. Existing traffic monitoring solutions mostly rely on manual observation, which cannot reflect traffic conditions in real-time, and are limited by environmental and lighting conditions, resulting in insufficient accuracy. This dataset aims to assist researchers in developing more precise traffic congestion detection algorithms by providing high-quality nighttime traffic images. The dataset consists of high-resolution nighttime traffic images, captured using high-performance night vision cameras on major city roads. We have implemented strict quality control measures, including multiple rounds of labeling and expert review, to ensure each image is accurately labeled. The data is stored in JPG format for quick access and processing.
Dataset Insights
Sample Examples
170565f1**.jpg|2560*1920|252.48 KB
07546650**.jpg|1920*2560|564.81 KB
d1233b64**.jpg|4000*3000|554.20 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| traffic_congestion_level | string | Annotate the traffic congestion level based on the density of vehicles in the image. |
| number_of_vehicles | int | Total number of vehicles visible in the image. |
| vehicle_types | string | Types of vehicles in the image, such as cars, trucks, buses, etc. |
| lighting_conditions | string | Description of lighting conditions in the image, such as darkness, shadows, streetlight illumination, etc. |
| weather_conditions | string | Weather conditions depicted in the image, such as sunny, rainy, foggy, etc. |
| road_type | string | Type of road shown in the image, such as highway, urban road, etc. |
| vehicle_color_distribution | string | Classification and number of vehicle colors in the image, such as red 3 vehicles, blue 2 vehicles, etc. |
| road_signs_present | boolean | Indicates whether road signs are visible in the image. |
| vehicle_speed_estimation | float | Estimated speed of vehicles in the image (in km/h). |
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 is the Highway Night Traffic Congestion Recognition Dataset?
- The Highway Night Traffic Congestion Recognition Dataset is a high-quality image dataset used to identify traffic congestion on highways during nighttime, aiding in the research and application of intelligent transportation systems.
- What application scenarios is this dataset suitable for?
- The dataset is mainly applied in the development of intelligent transportation systems to enhance the efficiency of nighttime traffic monitoring and congestion management.
- What types of data does the dataset include?
- The dataset includes highway images taken at night, intended for object detection to identify traffic congestion.
- How can this dataset be used for research?
- Researchers can use this dataset for model training, testing, and optimization of traffic congestion detection algorithms, particularly focusing on recognition performance in low-light conditions.
- Why is the recognition of highway night traffic congestion important?
- Identifying traffic congestion on highways is crucial for reducing accident risks, enhancing traffic flow management efficiency, and improving travel experiences, especially under nighttime conditions.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Highway Nighttime Traffic Congestion Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/c689b542f98e5e7c177765e0c6fb9d8b},
urldate={2025-09-15},
keywords={traffic congestion recognition, nighttime traffic dataset, target detection dataset},
version={1.0}
}Using this in research? Please cite us.
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