Nighttime Road Traffic Inspection and Risk Assessment Scenario Image Dataset
#Object Detection #Scene Recognition #Anomaly Detection #Traffic Monitoring #Safety Inspection #Risk Assessment
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
In the current transportation industry, nighttime traffic monitoring faces challenges such as road safety hazards and increasing accident rates. Existing monitoring systems struggle to effectively identify traffic risks in nighttime environments, leading to frequent accidents. To improve nighttime traffic safety management, this dataset is constructed to provide high-quality nighttime road scene images, helping researchers and developers enhance the performance of object detection algorithms. The dataset includes various nighttime traffic scenarios, including vehicles and pedestrians under different lighting conditions. Data collection uses high-performance cameras in urban roads and highways, ensuring data diversity and realism. Through multiple rounds of annotation and expert review, data quality is strictly controlled. The data is stored in JPG format, organized such that each image contains its corresponding annotation information, facilitating subsequent model training and testing.
Dataset Insights
Sample Examples
66297413**.jpg|1707*1280|334.38 KB
ce9d6879**.jpg|3000*4000|1.12 MB
04599b9e**.jpg|3000*4000|1.05 MB
19614478**.jpg|2560*1702|516.27 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| image_brightness | float | The overall brightness level of the image, typically ranging from 0 to 1, with values closer to 1 indicating higher brightness. |
| image_contrast | float | The degree of difference between the light and dark areas in the image, with higher values indicating greater contrast. |
| vehicle_count | int | The number of vehicles identified in the image. |
| pedestrian_count | int | The number of pedestrians identified in the image. |
| traffic_light_presence | boolean | Indicates whether there is a traffic light present in the image. |
| road_condition | string | The condition of the road shown in the image, such as wet, dry, etc. |
| weather_condition | string | The weather conditions present at the time the image was captured, such as clear, rainy, or foggy. |
| lighting_condition | string | The lighting conditions when the image was taken, such as bright, dim, or unlit. |
| incident_severity | int | The severity of any incident seen in the image, usually represented by a numerical value. |
| image_clarity | float | The clarity of the image, potentially rated on a scale from 0 to 1, with higher values indicating clearer images. |
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 types of nighttime traffic scene images are included in this dataset?
- This dataset includes various nighttime traffic scenes, such as road inspection and risk screening sites.
- How can this dataset be used to improve the performance of object detection algorithms?
- By providing diverse nighttime scenes and realistic traffic environments, the dataset can be used to train and test object detection algorithms, enhancing detection accuracy under nighttime conditions.
- What fields of traffic research and applications is this dataset suitable for?
- This dataset is suitable for research and applications in traffic monitoring, autonomous vehicle technology, and intelligent transportation systems.
- Why choose nighttime traffic scenes for data collection?
- Nighttime traffic scenes present higher detection difficulties and challenges, providing crucial data support for testing and optimizing algorithm robustness.
- What traffic safety issues can this dataset help address?
- By improving object detection techniques, this dataset may help identify and prevent nighttime road traffic incidents, thereby enhancing traffic safety.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Nighttime Road Traffic Inspection and Risk Assessment Scenario Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/7f2492fe126b9764c002df17c5953444},
urldate={2025-09-15},
keywords={Nighttime Traffic Dataset, Object Detection, Traffic Monitoring, Risk Assessment},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder