Autonomous Vehicles
Access accurate, high-quality training data to power your autonomous vehicles for a smooth, safe driving experience.
Looking for Data Annotation to power your autonomous vehicle project across the UK, US, Europe and Africa? Aya Data partners with you to deliver quality training data, accelerating AI and machine learning success. Achieve your AI goals with us!
Powering AI for Self-Driving Vehicles
We provide high-quality, human-in-the-loop data annotation services to power AI-driven self-driving vehicles. Our expert team ensures precise, structured, and error-free datasets for computer vision, smart navigation, and AI-assisted traffic management. With industry-leading expertise and scalable solutions, we help autonomous vehicle systems recognize pedestrians, roads, signs, and more – enhancing safety, efficiency, and innovation in transportation.
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For Your Autonomous Vehicles
We provide expert AI services for autonomous vehicles, including data annotation, acquisition, and consulting. Our solutions enhance perception, decision-making, and real-world performance for safer, smarter self-driving systems.
Data Annotation
Our expert team accelerates autonomous vehicle AI with precise data annotation. From bounding boxes for object detection to 3D point clouds for LiDARs, we create high-quality training data for safer, smarter self-driving systems. Our solutions power AI perception, ensuring accurate scene understanding, lane detection, and real-time decision-making in complex environments.
Data Acquisition
We acquire high-quality data for autonomous vehicle AI from diverse sources, including sensors, cameras, and LiDARs. Our team collects, processes, and curates real-world and synthetic datasets to enhance AI training. By leveraging simulation tools, we generate realistic driving scenarios, enabling cost-effective, scalable model development for safer and more reliable self-driving systems.
AI Consulting
Our AI experts collaborate with you to develop tailored solutions for autonomous vehicle AI. From perception and decision-making to sensor fusion and simulation, we help optimize your models for real-world performance. Whether refining algorithms or enhancing system efficiency, we ensure your self-driving technology is intelligent, adaptive, and road-ready.
OUR NETWORK
Leverage Aya Data’s Autonomous Vehicle Domain Network
Developing AI for autonomous vehicles demands specialized industry expertise. That’s why we collaborate with automotive engineers and mobility experts to refine our data annotation processes, validate outputs, and ensure AI models accurately perceive road environments, enhancing safety, efficiency, and real-world performance.
Data Annotation for the Autonomous Vehicles Industry
We provide precise robotic data annotation services for advanced movement training, from delicate object handling to specialized tasks.
Bounding Boxes for Object Detection
Our experts use bounding box annotation to train AI models in object detection for autonomous vehicles. By outlining objects with precise coordinates in images and videos, we help machine learning algorithms accurately identify, localise, and measure distances – enhancing a vehicle’s perception for safer navigation in complex driving environments.
Polygon Annotation for Irregular Shapes
Our polygon annotation service enables autonomous vehicles to recognise irregularly shaped objects with precision. By plotting multiple vertices along exact edges, we help AI detect motorcycles, bicycles, animals, and road elements. This enhances computer vision, ensuring safer navigation and collision avoidance in complex driving environments.
LiDAR Annotation
Our LiDAR annotation service enhances 3D perception for autonomous vehicles. By labeling 360-degree images and 3D point clouds, we help AI accurately map surroundings, detect objects, and track movement. This enables self-driving systems to navigate safely, avoid collisions, and make real-time driving decisions with high precision.
Semantic Segmentation for Image Classification
Our semantic segmentation service enables precise image classification for autonomous vehicles. By annotating every pixel with semantic information, we help AI differentiate objects, recognise road elements, and enhance perception. This technique ensures accurate scene understanding, allowing self-driving cars to detect and respond to their environment with greater reliability.
Object Tracking
Our data annotation services enable precise object tracking for autonomous vehicles by labeling and monitoring objects across video frames. Using techniques like bounding boxes and 3D point clouds, we help AI track pedestrians, vehicles, and other road elements in motion. This enhances situational awareness, ensuring safer navigation and real-time decision-making.
Polyline Annotation for Lane Detection
Our data annotation services enable precise object tracking for autonomous vehicles by labeling and monitoring objects across video frames. Using techniques like bounding boxes and 3D point clouds, we help AI track pedestrians, vehicles, and other road elements in motion. This enhances situational awareness, ensuring safer navigation and real-time decision-making.
Use Cases
Discover how data annotation enables precise perception, real-time decision-making, and safer navigation for autonomous vehicles through accurate object detection, lane recognition, and sensor fusion.
Object Detection
We label vehicles, pedestrians, and obstacles in images and videos, training AI to recognize and classify objects for safer navigation.
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Lane Detection
We use polyline annotation to define lane boundaries, road edges, and traffic patterns, enabling AI to interpret road structures and maintain proper lane positioning.
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Traffic Sign Recognition
We use semantic segmentation to annotate road signs and signals, helping AI accurately interpret traffic rules and enhance autonomous vehicle decision-making.
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Pedestrian Tracking
We use bounding boxes and polygon annotation to label pedestrians across video frames, allowing AI to track movement and predict behavior for accident prevention.
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Sensor Fusion
We use 3D point cloud annotation to enhance LiDAR and radar data, enabling AI to merge multi-sensor inputs for a complete understanding of surroundings.
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Autonomous Parking
We use bounding boxes and 3D cuboid annotation to help AI detect parking spaces, assess distances, and execute precise, collision-free parking maneuvers autonomously.
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Selected Case Studies
We help businesses of all sizes effectively navigate their AI journey.
What Our Clients Say About Us
The Aya Advantage
1/ Exceptional Customer ExperienceExceptional Customer Experience
Unwavering Quality
Unparalleled Subject Matter Expertise
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Featured News and Insights
Enjoy featured articles and insights from our experts.
Everything You Need to Know About Bounding Boxes
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iMerit Alternatives For Data Annotation
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Semantic Segmentation for Computer Vision Projects Explained
Frequently Asked Questions
What types of data do you provide for autonomous vehicle development?
Can Aya Data handle large-scale data annotation projects for autonomous driving?
What quality control measures are in place during the annotation process?
How is your autonomous vehicle data collected and processed?
Do you provide custom datasets for specific AV use cases?
What formats do you deliver autonomous vehicle data in?
How do you ensure data privacy and compliance in autonomous vehicle datasets?
What is the turnaround time for an autonomous vehicle data annotation project?
What experience does Aya Data have in the autonomous vehicle industry?
How does Aya Data stay updated with the latest trends in autonomous vehicle technology?
Simplify Your AI Development Today!
Do you need help with Data Acquisition, Data Annotation or building a custom AI model? Aya Data is ready to partner with you. Talk to us today!
