POSE: Phase II: CONNECT: Consortium of Open-source plaNNing models for Next-generation Equitable and efficient Communities and Transportation

Arizona State University, Scottsdale AZ

Investigators

Abstract

This project, funded by Pathways to Enable Open-Source Ecosystems (POSE), aims to promote a healthy and equitable society with diverse mobility options by addressing traffic congestion, air quality, and sustainability issues through efficient and effective multimodal transportation planning. The project will achieve this by extending the General Modeling Network Specification (GMNS) to GMNS+ through the Consortium of Open-Source Multimodal PlaNNing for Equitable and Sustainable Communities and Transportation Systems (CONNECT). The project's novel features include integrating a multimodal network modeling approach, ensuring equity among diverse communities, employing cross-resolution strategies, offering personalized mobility options, and utilizing time-sensitive network data. Additionally, the project will establish an extensive open-source ecosystem for a wide range of transportation solutions. Its impacts encompass fostering efficient, sustainable, safe, accessible, and inclusive transportation systems and facilitating informed decision-making at national, state, and city levels. With numerous Metropolitan Planning Organizations and Regional Councils in the United States, the project's streamlined process and open-source ecosystem will support informed decision-making at various governance levels. The research team adopts a technical approach that capitalizes on existing data formats to create seamlessly integrated multimodal networks, fostering offline and real-time data sharing among agencies and software packages. This strategy empowers the execution of dynamic multimodal analysis, heralding a new age of standardized data in transportation science, and making the examination of extensive multimodal datasets more approachable through a versatile and adaptable tool—potentially transforming data science within transportation. The team aims to integrate open data specifications with system optimization tools to optimize efficiency and equity within the urban transportation infrastructure community. By implementing sustainability governance, the project will strengthen the connection between real-world challenges faced by practitioners and the research community, ensuring product competitiveness and overall sustainability. The GMNS+ ecosystem holds the potential to significantly impact data science by facilitating the study of large multimodal datasets using innovative, highly flexible, and scalable computational and educational tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.