Abstract Manager

Artificial intelligence (AI) is increasingly being integrated into transportation infrastructure planning, design, and asset management to enhance analytical capabilities and decision support. Recent advancements in Building Information Modeling (BIM), digital twins, and transportation analytics platforms have created opportunities to directly incorporate AI within engineering design environments, enabling more data-driven approaches throughout the infrastructure lifecycle.

Despite its potential, deploying AI within production transportation design tools presents several technical and organizational challenges. These challenges include ensuring data quality and consistency, achieving interoperability with established digital workflows, and effectively integrating AI-generated outputs into existing engineering and governance processes. Addressing these issues is essential to ensure that AI enhances rather than disrupts traditional engineering decision-making practices.

The objective of this presentation is to examine how AI functionality is being embedded in transportation design and analysis tools to enhance conventional engineering workflows. The session aims to demonstrate how AI can improve predictive analytics, scenario evaluation, and performance-based design assessment while maintaining alignment with established transportation engineering practices.

The presentation draws on applied use cases and practical experiences from real-world implementations of AI within transportation design environments. It describes how AI techniques are integrated with BIM, digital twins, and transportation analytics and visualization platforms to support predictive analysis, alternative evaluation, and better alignment between design intent and observed or anticipated system behavior. Additionally, it discusses approaches used to mitigate challenges related to data, workflows, and integration.

Through demonstrated applications and measurable outcomes, the presentation shows that AI integration within transportation design tools can enhance insight generation and support more informed engineering decisions. These capabilities contribute to improved analytical depth, better contextual understanding of design alternatives, and the delivery of more resilient and sustainable transportation infrastructure.