NSF Award
2213946
The broader impact/commercial potential of this Partnerships for Innovation – Research Partnerships (PFI-RP) project is improved transportation safety and usability for the general public during adverse weather conditions. Additionally, this project seeks to develop and commercialize new computer vision and machine learning techniques that can be applied to other applications, facilitating engagement from the automotive industry in addressing inclement weather driving problems and enabling entrepreneurial engagement from underrepresented communities. Achievement of safe vehicle operation in adverse weather has further implications associated with the widespread deployment of automated vehicles and features including improved efficiency to combat climate change, improvements in ground vehicles for military applications, and a stronger transportation network design and management. Students from underrepresented communities will be recruited and receive training in translational research and entrepreneurship through engagement with existing university-wide organizations.<br/> <br/>The proposed project seeks to develop automated vehicle computer vision for adverse weather which, despite being commonly identified as a needed product, has received relatively little attention in the marketplace. The proposed technology utilizes automotive cameras, computer vision, systems engineering principles, and refined methods of machine learning without an overreliance on deep learning. The translation and commercialization of computer vision algorithms into a fully automated vehicle systems with embedded hardware requires a multidisciplinary approach requiring academic, industrial, and entrepreneurial competence. The four key technical barriers include data scale-up, module improvements, vehicle integration, and use of embedded hardware. Because the identified minimum viable product is designed for safe automated driving in snow, the team is pursuing winter season milestones that include large dataset collection, module improvements with an associated vehicle integration demonstration, and a complete minimum viable product demonstration with potential business partners and customers. The project goal is successful commercialization of an automotive lane line detection software for snow-covered roads.<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.
