NSF Award
2431309
This Civic Innovation Challenge (CIVIC) Stage 1 project will support research that intends to develop and provide a roadmap for revitalizing legacy rail lines—which are abandoned, out-of-service, or underutilized railroad tracks. There are thousands of miles of existing but underused legacy lines in urban and rural communities across the country. This existing infrastructure is poised to improve accessibility by better connecting underserved communities to essential services. The primary barrier to using legacy rail lines is the lack of affordable rail-defect detection systems, which are important safety mechanisms. This research project aims to overcome that barrier. The project team — academic, civic, community, and industry partners — will use Philadelphia’s Delaware River waterfront as a demonstration site using a low-cost, artificial intelligence-based technology previously developed by the team. This technology, which is installed onboard trains, detects broken rails and other track damage in near real-time, facilitating a transition of a legacy line to active passenger rail in months rather than years. Research completed in association with project is the culmination of a decade-long process of public engagement and research, identifying rail as the preferred choice for improving accessibility because it better connects with other transit modes, supports high-capacity needs, stimulates local economies, adapts to increasing demand, offers more reliable service, and produces fewer emissions per passenger than cars and buses. By repurposing dormant rail assets, the project aims to enhance connectivity, reduce traffic congestion, promote environmentally friendly transportation, revitalize communities, and improve living standards in both urban and rural settings.<br/><br/>To achieve these goals, the research will strive to reintroduce affordable, dynamic, and community-driven legacy rail systems by transitioning new, safe technologies into an industry traditionally adverse to rapid change. The onboard monitoring and detection technology deployed and tested through this project combines two complementary sensing modalities: real-time acceleration data to inform statistical anomaly detection algorithms and real-time automated computer vision for detecting broken rails and classifying track damage. This adaptable system provides actionable data on integrity and ridership, reducing the time and financial barriers compared to traditional rail upgrades, and facilitating quicker regulatory approval and community acceptance. In Stage 1, this research project will: (1) integrate this technology within passenger rail intending to demonstrate that it is adaptable to various types of trains and locations, (2) assess the economic impacts of revitalized legacy rail, (3) gain community feedback on implementation needs, and (4) address the regulatory, financial, and governance implications of deploying advanced technologies for revitalizing legacy rail infrastructure. <br/><br/>This project is in response to the Civic Innovation Challenge program’s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.<br/><br/>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.
