Work

Automated Driving Construction Vehicle for Lane Line Repainting

Year: 2025

Type: article

Abstract: This paper presents an advanced vision-based lane repainting system for smart road maintenance. The system integrates a YOLO-based deep neural network for lane detection and the Pure Pursuit Algorithm for precise path tracking and repainting. It ensures robust performance in detecting faded, dashed, or partially damaged lane markings while maintaining accurate alignment. A multi-camera setup enhances lane recognition and nozzle positioning, improving painting precision. Planned field tests on highways will evaluate its effectiveness in real-world conditions, demonstrating its contributions to safer and more efficient smart lane maintenance.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.07.027

Authors: Junghyun Choi, Kanghyun Nam, Youngsik Jin

Institutions: Keimyung University, Yeungnam University, Electronics and Telecommunications Research Institute

Language: English

Topic: Autonomous Vehicle Technology and Safety

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funders: Electronics and Telecommunications Research Institute, National Research Foundation of Korea, Ministry of Science and ICT, South Korea