Which specific area of pavement management can benefit most from the use of artificial intelligence?

Pavement performance modeling and prediction can benefit the most from the use of artificial intelligence (AI) and machine learning (ML). AI/ML algorithms can analyze large datasets of pavement condition, traffic loading, environmental factors, and other relevant variables to develop more accurate and reliable pavement performance models. Traditional pavement performance models are often based on regression analysis or mechanistic-empirical methods, which can be limited in their ability to capture the complex relationships between these factors and pavement performance. AI/ML algorithms, such as neural networks and support vector machines, can learn these complex relationships from data without the need for explicit assumptions about the underlying physical mechanisms. This allows AI/ML models to provide more accurate predictions of pavement condition over time, enabling pavement managers to make more informed decisions about maintenance and rehabilitation strategies. For example, AI/ML models can be used to predict the optimal timing for applying preventive maintenance treatments or to identify pavement sections that are at high risk of failure. The improved accuracy and reliability of AI/ML-based pavement performance models can lead to significant cost savings and improved pavement network performance.