Safe Accessible Multimodal Mobility Intelligence (SAMMI) for All Road Users

The proposed Safe and Accessible Multimodal Mobility Intelligence (SAMMI) project aims to revolutionize Complete Streets development with an AI-driven decision support system. SAMMI addresses the lack of a comprehensive, data-driven approach to identifying and prioritizing complete streets projects, which currently relies on limited data and historical crash information, delaying interventions. The SAMMI system will integrate diverse data sources on travel behavior, infrastructure conditions, and environmental context to provide actionable insights for proactively identifying high-priority complete streets projects. By leveraging emerging technologies, such as computer vision and machine learning, SAMMI will enable efficient data generation and analysis. The incorporation of Generative AI techniques will enhance the accessibility of design standards and guidelines, streamlining the planning process. The Phase I effort will focus on establishing a foundation for SAMMI by understanding user requirements, demonstrating data generation capabilities, and exploring GenAI data processing techniques. A proof-of-concept report will be developed to validate the approach and lay the groundwork for Phase II prototype development. SAMMI has the potential to significantly improve safety, accessibility, equity and sustainability in transportation by empowering data-driven decision-making and accelerating the implementation of Complete Streets nationwide.