Shaping the Future of Transportation with Computer Vision

Revolutionize transportation with computer vision for smarter, safer, and more efficient systems.
Try  for free
Talk to sales
Collage of urban street scenes with multiple vehicles, pedestrians, bicycles, and dogs, each labeled with bounding boxes and tags including car, person, bicycle, and dog.

Data Annotation for Transportation

Enhance transportation systems with precise data annotation, enabling smarter navigation, traffic management, and operational efficiency.
3D LiDAR point cloud visualization showing a blue autonomous car detecting multiple human figures and objects in its surroundings enclosed in colored bounding boxes.

3D Lidar

3D LiDAR annotation provides precise spatial information by labeling point cloud data, enabling accurate object detection, classification, and tracking for applications such as autonomous vehicles, robotics, and smart city systems. This advanced annotation type captures depth, shape, and distance, essential for building robust AI models.
Two large trucks followed by several cars driving on a multi-lane highway with green 3D bounding boxes around each vehicle.

3D Cuboid

3D Cuboid annotation involves creating three-dimensional bounding boxes around objects, capturing their position, orientation, and size in a 3D space. This technique is essential for training AI models in applications like autonomous driving, robotics, and augmented reality, enabling accurate object detection and spatial understanding.
Heavy traffic jam on a multi-lane road with cars, motorcycles, buses, and trucks detected and labeled with colored boxes.

Predict and Mitigate Real-Time Traffic Issues

Enable AI systems to predict and mitigate real-time traffic issues through advanced data annotation. By accurately labeling vehicles, road signs, lane markings, and traffic patterns, this annotation type empowers smarter navigation, congestion management, and safer transportation solutions.
Rear view of a white Peugeot RCZ car parked on cobblestone, with license plate number 6910 TE-7 and country code BY.

License Plate Reading

Promote your services and let potential customers purchase your products in a highly-structured mode.
Urban street scene with multiple 'Do Not Enter' signs, no bicycles allowed, and no pedestrian crossing signs on a city street with traffic and tall buildings.

Road Signs Reading

Road Sign Reading annotation involves labeling and classifying various road signs in images or video data. This annotation type is essential for training AI models in autonomous vehicles, traffic management, and navigation systems, ensuring accurate sign detection and improved decision-making on the road.
Pedestrians crossing a street at a crosswalk, each person highlighted with green detection boxes.

Monitor Pedestrians and Foot Traffic

Monitor Pedestrians and Foot Traffic annotation involves accurately labeling and tracking people in various environments. This annotation type is crucial for applications such as smart city planning, autonomous vehicles, crowd management, and safety analytics, enabling intelligent systems to understand and respond to human movement.
Close-up of damaged asphalt road surface showing a pothole with exposed underlying layer.

Monitor Road and Infrastructure Conditions

Monitor Road and Infrastructure Conditions annotation involves labeling and analyzing road surfaces, infrastructure elements, and environmental factors. This annotation type is essential for maintaining road safety, optimizing infrastructure management, and supporting autonomous vehicle navigation with accurate data insights.

Save Both Time and Money!

Save Both Time and Money!

Discover why Unitlab AI stands out as the ultimate solution for your data annotation needs.

15X

Faster Data Annotation
Orange square with a white check mark inside a white circle.
Auto Data Collect
Orange square with a white check mark inside a white circle.
Auto Data Labeling
Orange square with a white check mark inside a white circle.
Auto Model Validation
Orange square with a white check mark inside a white circle.
Auto QA
Orange square with a white check mark inside a white circle.
Auto Model-In-the-Loop

60%

Free Up AI Engineer’s Time
Orange square with a white check mark inside a white circle.
Dataset Curation
Orange square with a white check mark inside a white circle.
Dataset Version Control
Orange square with a white check mark inside a white circle.
Dataset QA
Orange square with a white check mark inside a white circle.
AI Model Integration
Orange square with a white check mark inside a white circle.
AI Model Validation

5X

Save AI Development Cost
Orange square with a white check mark inside a white circle.
5X saving in Data Collection
Orange square with a white check mark inside a white circle.
10X saving in Data Labeling
Orange square with a white check mark inside a white circle.
5X saving in Dataset Curation
Orange square with a white check mark inside a white circle.
5X saving in AI Development
Orange square with a white check mark inside a white circle.
5X saving in Model Validation

Annotation types for Transportation

Explore diverse annotation types for transportation, including vehicle detection, lane marking, traffic sign recognition, and route mapping to power advanced AI solutions.
Busy multilane city street with numerous cars, a person riding a bicycle, and several pedestrians near the crosswalk.

Bounding Box for Object Detection

Self-driving vehicles depend on their ability to perceive their environment for safe navigation. Experts play a key role by annotating bounding boxes, helping the vehicle's computer vision system accurately assess the distance and size of objects on the road and along the sides.

Segmentation for Object Classification

Semantic segmentation enhances object detection in autonomous vehicles by grouping multiple objects of the same category as a single unit. This process involves classifying every pixel in an image based on its semantic meaning, such as identifying all cars or all people within the scene.

Street scene with multiple color-segmented vehicles including SUVs and cars, green road, red buses, and trees along city buildings.
Rear view of a white Honda car driving on a highway with a green line and dots graphic overlay following the road.

Polyline Annotation for Lane Detection

Autonomous vehicles rely on environmental perception to navigate safely. Specialists contribute by marking bounding boxes, enabling the vehicle's computer vision system to accurately determine the size and distance of objects on and around the road.

Polygon for Shapes

Access expert assistance to accurately trace polygons around irregularly shaped objects. This enables computer vision systems in autonomous vehicles to detect all visible objects on the road, such as motorcycles, bicycles, cars, and animals, ensuring safe driving by preventing collisions.

Small green hatchback car parked partially on a paved shoulder beside a highway guardrail.

FAQs

Is Unitlab a free Data Annotation Tool?

Yes, it is! No credit card is required to use Unitlab. You can use the Unitlab tool for free forever as long as you stay within the set limits. However, for more extensive use, Unitlab offers a subscription model. This model's pricing is customized to your organization's specific usage, data requirements, and any extra services you might need, like our advanced labeling solutions. To get a tailored quote and further information, please connect with our sales team.

Can I switch my plan after I create my account?

Yes, you can start working with a Free Plan and then change plans in the future as you evaluate which is best for you.

How is the Price of a Data Labeling Service Calculated?

Data Labeling Services start at just $0.02 per image. The base price depends on the types of data annotation, the number of classes, and the average number of objects to annotate per image.

How Can I Set Up the Unitlab On-Premises Solution in My Local Workspace?

Unitlab offers a range of scalable On-Premises solutions! Contact Us to discuss your requirements. You can purchase Unitlab's On-Premises solution after consulting with us. We help you install our entire annotation system in your workspace.

Didn’t find the answer you are looking for? Contact our support
YouTube play button icon with dark circular background.Facebook logoLinkedIn logo

Products

Data AnnotationDataset  ManagementModel ManagementLabeling ServiceOn-Premises Solutions

Solutions

FintechHealthEducationAgricultureE-CommerceDronesAugmented RealityRoboticsVideo SurveillanceFacial RecognitionLogisticsTransportation

Resource

PricingBlogDocs HubFeature RequestChangelogs

Company

About usPrivacy TermsCookie Policy
©2025 Unitlab, Inc. All rights reserved.