Hyundai on its autonomous driving data collection, testing, and development

Hyundai Motor Group has put its Data Flywheel into full operation, a system the OEM says collects data and trains, validates, and deploys AI.

“The Data Flywheel operates as a virtuous cycle in which data collected from vehicles is used to train and validate AI models, with improved models subsequently deployed back to vehicles to generate new data,” a Hyundai press release states. “The Group also benefits from significant advantages at the starting point of the Data Flywheel: data acquisition.”

Hyundai presented its autonomous driving development strategy, technology roadmap, and implementation plans at the group’s HMG Autonomous Driving Media Day in Korea earlier this month.

The group says that integrated data and AI systems form the foundation for its next-generation vehicle technology, with the Data Flywheel as a key element of its autonomous driving competitiveness.

42dot, a smart mobility solutions company covering vehicle operating systems, AI agents, autonomous driving AI, and other areas, also introduced key technologies during the Media Day for Hyundai Group vehicles. 42dot shared development progress for proprietary autonomous driving AI, Atria AI, and outlined the background and plans for its Vision-Language-Action (VLA) technology development initiative.

Video footage was shown during the Media Day of an Atria AI-equipped software-defined vehicle (SDV) navigating complex urban traffic without driver intervention. Operating at a Level 2++ capability, the autonomous driving system illustrates how the Data Flywheel enables a continuous cycle of learning, validation, and performance improvement, the Hyundai release states.

“Autonomous driving competition is no longer about comparing specific features,” said Minwoo Park, Hyundai Motor Group Advanced Vehicle Platform Division president/head and 42dot CEO, in the release. “Competitiveness is determined by how much data you secure, how quickly you learn, and how effectively you can reflect those results in actual products and services.

“At its core, autonomous driving competitiveness comes down to having systems that enable continuous, rapid learning. Hyundai Motor Group will develop autonomous driving technology that customers can trust, based on a virtuous cycle of data, AI, and validation. Our goal is to ensure the safety and quality levels customers can trust while we learn and improve rapidly.”

In March, Hyundai Motor Group announced a collaboration strategy with NVIDIA, introducing a dual-track approach that the companies said combines the rapid deployment of proven autonomous driving technologies with the development of proprietary AI capabilities.

Hyundai says it will integrate NVIDIA’s validated vehicle AI computing platform and autonomous driving software into its SDV architecture, prioritizing accelerated deployment while building a foundation for scalable data-driven development.

The integration is planned in two tracks, the first including:

• • Production vehicles equipped with NVIDIA solutions-based Level 2+ autonomous driving capabilities are targeted for the first half of 2028, and a Level 2++ production vehicle is targeted for the second half of 2028.
  • Progressive standardization of sensor systems used across Hyundai Motor, Kia, 42dot, and Motional around NVIDIA DRIVE Hyperion 10
  • More consistent data collection and utilization for AI training and validation

The second track will include:

• • Production of Atria AI-powered Level 2++ vehicles slated for the second half of 2029
  • Phased progression of autonomous driving capabilities based on real-world driving data collected from production vehicles

“This dual-track strategy enables the Group to deliver advanced capability to customers in the near-term while building sustainable technology advantage for the future,” the release states.

The release notes that Hyundai Motor and Kia sell more than 7 million vehicles annually across 190 countries and regions worldwide.

“This global production footprint provides a foundational advantage for autonomous driving data collection,” the release states. “Currently, the Group operates approximately 40 dedicated data collection vehicles around the clock to gather driving data.”

It adds that the collected datasets include routine driving scenarios and a wide range of real-world edge cases, including: road construction zones and infrastructure variations; severe weather conditions; abrupt lane changes and emergency maneuvers; parked vehicles on side streets and narrow roads; complex urban traffic dynamics; and advanced learning techniques.

“While large volumes of driving data are important, autonomous driving AI performance is not determined by data volume alone,” the release states. “Model advancement depends on how effectively developers can identify situations that challenge AI systems and focus learning on those scenarios.”

To accelerate AI model improvement, Hyundai says it has been integrating new technologies into its Data Flywheel since earlier this year, including:

• • “Hard Example Mining — Automatically identifies challenging driving situations, or edge cases, that AI models find difficult to recognize or interpret, and prioritizes those scenarios for training.
  • “Continuous Training Pipeline — Continuously incorporates newly acquired data from real-world driving and validation processes into model training, enabling repeated performance improvements over time. Vehicle evaluation findings are fed back into data collection and model development, shortening development cycles and accelerating model refinement.
  • “Virtual Validation Technology — Virtual validation is another key component of the Data Flywheel. Hyundai Motor Group reconstructs real-world driving data into three-dimensional environments and utilizes advanced graphics technologies such as 3D Gaussian Splatting to recreate scenarios that are difficult or potentially unsafe to reproduce through real-world testing. This enables engineers to repeatedly evaluate models across diverse edge cases while verifying that newly trained models do not degrade existing performance.
  • “Follow-the-Sun Development — Connecting development centers in South Korea and the U.S., the Group operates a Follow-the-Sun development model. By leveraging differences in time zones, teams sequentially carry out data collection, issue analysis, and model improvement activities, enabling continuous 24-hour development.
  • “Special Event Recorder (SER) Integration — The Group is also gradually integrating its Special Event Recorder (SER) into the Data Flywheel. SER is a system that automatically records and stores significant events and related data that occur during autonomous driving.”

According to Hyundai, the recorded data is primarily used to support AI model training and performance improvement. It says the Group is exploring ways to enhance SER so AI models can more effectively identify challenging edge cases and automatically secure relevant datasets required for performance improvements.

Alongside mass-production technology development, the Group says it’s pursuing real-world Level 4 autonomous driving validation. In partnership with South Korea’s Ministry of Land, Infrastructure and Transport, the Group plans to deploy the Atria AI-equipped SDV Pace Car in Jeonnam-Gwangju Special Metropolitan City, South Korea, by year-end.

This pilot project will operate autonomous vehicles in Korean road environments characterized by complex traffic dynamics and unpredictable variables, and feed the captured data directly into the Data Flywheel for AI learning and performance improvement.

“Through the data flywheel system now in full operation, we expect continuous improvement of issues identified on real roads and rapid technology advancement,” said Junghyun Kwon, Hyundai Motor Group Autonomous Driving Development Center executive vice president/head and 42dot Autonomous Driving Division lead, in the release.

Seonggyun Jeong, 42dot’s Atria Group lead, added: “Good autonomous driving AI ultimately starts with high-quality data. Hyundai Motor Group continuously improves the performance and maturity of Atria AI through an integrated development cycle that spans data collection, model training, and real-world vehicle validation.”

42dot plans to develop Vision-Language-Action (VLA) models alongside its existing end-to-end (E2E) autonomous driving models, which it says will enhance the stability and scalability of autonomous driving technologies while providing a range of solutions tailored to different vehicle hardware specifications and customer needs. 42dot is also applying the Data Flywheel to VLA development.

“When driving issues arise, the team analyzes the root cause, reinforces the relevant driving policies and data, then retrains the model to improve performance,” the release states.

42dot’s VLA-based autonomous driving technology is in the simulation-based model validation stage.

The Group plans to activate the full development process, including real-vehicle testing, from late 2026 through early 2027.

“VLA is a core technology for implementing Physical AI where AI goes beyond simply driving to understand situations, reason through them, and act. Starting with autonomous driving, it will provide the foundation to expand into diverse fields such as robotics and beyond,” said HeeSeok Lee, 42dot’s Trion Group lead, in the release.

Images

Featured image: An Atria AI-equipped software-defined vehicle (SDV) is shown navigating complex urban traffic without driver intervention. (Provided by Hyundai Motor Group)

Secondary photos from the HMG Autonomous Driving Media Day held in Korea, September 2026. (Provided by Hyundai Motor Group)