---
title: "Real-Time Traffic Video Dataset"
description: "Traffic dataset featuring annotated video streams from cameras at urban intersections and crosswalks, designed for vehicle detection, pedestrian detection, and traffic monitoring in real-time traffic…"
url: "https://unidata.pro/datasets/real-time-traffic-and-environmental-video-dataset/"
date_modified: "2025-12-09T11:14:48+03:00"
language: "en-US"
---
Traffic dataset featuring annotated video streams from cameras at urban intersections and crosswalks, designed for vehicle detection, pedestrian detection, and traffic monitoring in real-time traffic scenarios with metadata on weather, time, and traffic events to support advanced traffic surveillance and traffic prediction models.

## Dataset Structure

### The Numbers Section

**Numbered list:** - **Number:** 500 — **Text:** Videos

### Tooltips Section

**Tooltip items:**

- **Name:** Auto
- **Name:** Computer Vision
- **Name:** Machine learning
- **Name:** Object Detection
- **Name:** Smart Cities

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Videos of fixed-angle urban traffic (intersections, crosswalks) for object detection tasks. |
| Data types | Video |
| Tasks | Detection, Classification |
| Number of video | 500+ |
| Marking | Bounding Box |
| Labeling | Metadata(time of day, weather (rain/snow/fog), vehicle/pedestrian counts, traffic light status) |
| Type of vehicles | Light vehicles (cars) and heavy vehicles (minivan) |

**Media Slider:**

- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/04/real-time-traffic-and-environmental-video-dataset-2.webp)
- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/04/real-time-traffic-and-environmental-video-dataset-1.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/12zSB4bXSbp4Q5KMD-imOwmnrYmDK-FjP?usp=sharing)

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Video Extension | MP4 |
| Extension of labeling file | JSON |
| Video Duration | 30 min - 1 hour |
| Video Resolution | Min = 1920×1080 |

**Source and data collection methodology:** Source and collection methodology. Data was collected by parsing videos from various sources

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Transportation Planning — **Title:** Optimizing Traffic Flows — **Text:** Real-Time Traffic Video Dataset provides extensive video streams from urban and highway traffic cameras, supporting traffic monitoring and traffic management initiatives. Researchers and planners can analyze vehicle counts, traffic density, and driving behaviors across real-world traffic scenarios, enabling data-driven decisions for road safety and transportation systems.
- **Industry:** Autonomous Vehicles — **Title:** Training Vehicle Detection Models — **Text:** This traffic video dataset enables the development of object tracking and vehicle detection models for autonomous driving applications. With annotations including vehicle types, tracks, and speeds, AI systems can learn to identify real-time objects, traffic signals, and pedestrians, improving safety and decision-making in dynamic traffic scenes.
- **Industry:** Traffic Safety and Surveillance — **Title:** Accident Detection and Incident Monitoring — **Text:** The dataset supports traffic surveillance by providing video sequences of traffic events, traffic accidents, and traffic signals in diverse conditions. Analysts can use this real-time traffic dataset to detect incidents, monitor traffic flows, and evaluate road segments, helping law enforcement and traffic authorities implement safety measures effectively.
- **Industry:** Smart City Analytics — **Title:** Predictive Traffic Modeling — **Text:** Using the traffic and environmental dataset, urban planners can develop traffic predictions and forecast vehicle counts, traffic volumes, and congestion patterns. The dataset’s video clips and real-world data across different road types and weather conditions allow for training machine learning models that enhance urban traffic management and intelligent transportation systems.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** What types of annotations are provided? — **Answer:** Annotations include bounding boxes for vehicles and pedestrians, traffic light status, vehicle classification (light or heavy), and scene metadata for traffic density and environmental conditions.
- **Question:** Can I request a sample of the traffic video dataset before purchase? — **Answer:** Yes. Unidata provides free sample video clips so you can evaluate the quality, labeling format, and dataset structure before accessing the full collection.
- **Question:** What are the sources of data for this dataset? — **Answer:** Data is collected by parsing publicly available urban traffic videos from multiple sources, including traffic cameras and surveillance feeds, ensuring coverage of diverse real-world scenarios.
- **Question:** How was the traffic data collected? — **Answer:** Videos are collected by parsing urban traffic recordings from multiple sources, capturing fixed-angle intersections, crosswalks, and urban roads. The data is verified for quality and usability for detection and classification tasks.
- **Question:** How are Unidata datasets licensed? — **Answer:** Unidata datasets follow a dual-licensing model: free samples are available for testing and evaluation, while full datasets are available exclusively for purchase, covering both research and commercial applications.
- **Question:** How long does it take to receive the dataset? — **Answer:** After submitting a request and completing necessary documents, the dataset is delivered within 3–10 days following payment and agreement finalization.
- **Question:** How are Unidata datasets stored? — **Answer:** Datasets are securely stored on AWS cloud infrastructure, providing high availability and scalability. Storage and management comply with ISO 27001 and ISO 27701 standards, guaranteeing privacy and security.
- **Question:** How can a traffic video dataset improve smart transportation systems? — **Answer:** A traffic video dataset helps AI models understand road environments, vehicle movement, and pedestrian behavior. It supports the development of intelligent transportation systems that can improve traffic monitoring, congestion analysis, and urban mobility management.
- **Question:** How does annotated traffic video data help train object detection models? — **Answer:** Annotated traffic videos provide labeled examples that allow computer vision models to learn how to identify and locate objects in road scenes. This improves model accuracy for detecting vehicles, pedestrians, and other important traffic elem

[Full list of this site's AI-readable pages](https://unidata.pro/llms.txt)