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SAI-P: Overcoming Barriers to User-Centered Infrastructure Planning with System Modeling and Natural Language Processing
Principal Investigator:
Antonie Jetter, Portland State University
Co-Investigators:
- Avinash Unnikrishnan, Portland State University
- Ameeta Agrawal, Portland State University
Summary:
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate humancentered fundamental and potentially transformative research that strengthens America?s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows th...
Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate humancentered fundamental and potentially transformative research that strengthens America?s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering. The U.S. transportation infrastructure is aging rapidly. Strengthening this infrastructure is a high priority for the nation. This SAI planning project focuses on how computer technology can improve transportation planning so that costly investments in infrastructure are successful and serve all members of a community. A major challenge in this area is that many transportation projects (bridges, highways, light rail lines) experience community push back, cost overruns, schedule delays, and lengthy approval processes. When such projects are completed, the results can sometimes be disappointing because the outcomes are not as good as expected. Projects can also negatively impact people who are poor, disabled, or marginalized in other ways. Transportation planners can avoid such problems by involving experts and community members early, learning from them, and anticipating outcomes. In doing so, however, planning teams can get overwhelmed by too much information about diverse concerns and opinions. This project addresses the problem by using technology to help planners process data more thoroughly. As a result, transportation projects will better serve user needs and produce more positive impacts for communities. This project harnesses recent advances in computing technology to help transportation planners process large volumes of complex data. Two technologies are combined in this project: Natural Language Processing (NLP) and Fuzzy Cognitive Mapping (FCM). NLP technologies assist in the processing and interpretation of texts (expert reports, community comments, posts on social media). FCM helps people understand causes and effects in complex situations. FCM is used in this project to help people understand the likely outcomes of a transportation plan. These technologies are combined to create a new transportation planning approach. A participatory framework brings experts, community members, and planners together to test and provide feedback on the new approach. This SAI planning activity develops and evaluates the technical foundations of the participatory planning method and designs plans for testing this approach in real-world planning situations to ensure it works in practice. This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Engineering. 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.
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Project Details
| Project Type: | Research |
|---|---|
| Project Status: | Completed |
| End Date: | November 30, 2025 |