"An AI-Driven Framework for Assessing Intersection Infrastructure and A" by Logan Liddiard, Joel Pierson et al.
 

Document Type

Poster

Journal/Book Title/Conference

National Conference of Undergraduate Research

Location

Pittsburgh, PA

Publication Date

4-9-2025

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Abstract

Background: Intersections serve as vital nodes within transportation networks, facilitating the movement of pedestrians. However, their effectiveness often hinges on the quality of their infrastructure and accessibility. Furthermore, it is expensive and time-consuming to collect infrastructure data, yet is crucial for creating a safe and efficient urban landscape.

Objective: Develop an AI-driven model that leverages Google Street View to provide detailed information about intersections, helping city planners identify infrastructure and accessibility issues and supporting improvements to create safer, more accessible intersections for people of all abilities.

Share

COinS