SUSTAINABLE HIGHWAY AND TRANSPORTATION SYSTEMS USING BIM & AI

Abstract

This study presents an integrated framework for developing sustainable highway and transportation systems through the combined use of Building Information Modeling (BIM) and Artificial Intelligence (AI). The proposed methodology leverages BIM for life-cycle data integration, while AI algorithms optimize design, construction, and maintenance processes for improved energy efficiency and resource utilization. A hybrid AI–BIM model is introduced to simulate traffic flow, predict pavement deterioration and assess carbon emissions across project stages. Real-time sensor data and predictive analytics are used to support decision-making in infrastructure resilience and asset management. The approach enables proactive maintenance scheduling, reduces environmental impacts, and enhances safety and cost-effectiveness in highway planning. The findings highlight the transformative potential of AI-enabled BIM systems in achieving sustainable transport infrastructure aligned with global smart city and green mobility goals.