RISE Industry-Academia Joint Research
Development and Demonstration of Unmanned Road Damage Restoration Technology
Building the world's first unmanned road pavement maintenance system combining AI robotics and advanced materials technology
AI Road Damage Detection Unmanned Restoration Robot Eco-friendly Repair Materials Integrated Control System
This is an Industry-Academia joint technology development project carried out together with KAIST, Seoul National University, and Rovoroad as part of the RISE (Regional Innovation System & Education) program.
Research Objectives
By combining AI robotics technology, lifecycle decision-making technology, and advanced materials technology, we aim to build the world’s first unmanned road pavement maintenance system that is fast, economical, and safe.
Background
- 94% of domestic roads are over 40 years old since construction
- Increasing heavy rain and snowfall; days with temperature variation exceeding 10°C increased 40% over the past decade
- Road repair budgets doubled over 8 years; public complaints increased 10-fold over 5 years
- Due to Jeju’s coastal climate and tourism characteristics, road damage directly affects the regional image
Core Technologies
- Real-time road condition monitoring: AI-based automatic road damage detection and classification
- Unmanned road damage restoration robot: Unmanned restoration process with no worker intervention
- Eco-friendly repair materials: High-strength, waterproof, high-durability alternative materials suited to Jeju’s climate characteristics
- Integrated control system: Restoration priority decision-making based on tourism and logistics vehicle movement pattern analysis
- Demonstration data-based commercialization model: Reduction of road damage-derived problems by 90% or more
Participating Institutions
| Institution | Role |
|---|---|
| Cheju Halla University (Lead) | Overall research management, AI system development |
| KAIST | Robot control and autonomous driving technology |
| Seoul National University | Road materials and advanced materials research |
| Rovoroad (Corporation) | Industry partner, demonstration and commercialization |
Cheju Halla University Student Researchers
Four student researchers from the Department of Artificial Intelligence participate in the development of the AI road damage detection system.
| Name | Role |
|---|---|
| 문재현 | Student Researcher |
| 김재은 | Student Researcher |
| 김웅빈 | Student Researcher |
| 홍성관 | Student Researcher |
- Development of AI-based road image analysis and damage classification models
- Construction of control system data pipelines
- Collection of demonstration data and performance evaluation
Project Information
- Research Period: July 2025 – February 2028 (3 years)
- Total R&D Budget: 900 million KRW
- Principal Investigator (PI): Professor Young Joon Lee, Department of Artificial Intelligence, Cheju Halla University