Cost-effective optimization system for automated asphalt pavement maintenance

Abstract

As road mileage and service life have increased, the annual road maintenance budget has increased progressively. To balance engineering specification requirements with the need to minimize construction costs, an optimized system for automated pavement maintenance is proposed. The system is comprised of modules for initial pavement evaluation, repair method selection, maintenance strategy determination, and iterative optimization. Subsequently, pavement parameters are input, MATLAB codes perform evaluations and strategy selections, while Python scripts automate background modeling, computation, and data transmission. The results are transmitted back to the algorithm to complete data interaction and optimization, resulting in the optimal maintenance strategy. A case study shows that when compared to traditional maintenance plans, this system can reduce costs by up to 27.33 % while maintaining pavement standards. The system improves the accuracy of fatigue life predictions and provides theoretical guidance for automatic pavement maintenance.