Safety-Driven Design: AI and Computer Vision for Enhanced Decision Support

Abstract: The rapid evolution of computer vision and artificial intelligence (AI) has led to technological developments to transform the transportation design process. These developments allow planners and engineers to make more informed, safety-driven decisions at all stages of the design process, from inception through to post-build monitoring.
By leveraging computer vision and AI, infrastructure conditions can be assessed and monitored to guide critical decisions not only for maintenance but for identifying and prioritizing safety interventions. These insights allow for more strategic maintenance programming based on infrastructure deterioration patterns that may lead to increased safety risk.
The design process and decision-making is further supported through AI by identifying conflicts and gaining valuable insights into the underlying causes of crashes. These driver behavior insights lead to more comprehensive, effective, and safety-centric design element selection.
Post-build performance assessments using these technologies are also available immediately upon completion of any improvement project to quickly validate the effectiveness of the design decisions and ensure no new safety risks were unintentionally introduced.
And finally, through continuous monitoring, these AI systems provide ongoing feedback, enabling timely responses to safety risks as (or even before) they arise.
This presentation will highlight how computer vision and artificial intelligence empower more data-driven, safety-focused design decisions that will help create infrastructure that not only meets today’s demands but anticipates and mitigates future safety challenges.