NSF Award
2032744
The broader impact/commercial potential of this I-Corps project is the development of safe automotive transportation in inclement weather. This project is based on the development of advanced computer vision algorithms that provide more reliable driving information in inclement weather. The improvements in vehicle operation from commercialization of this technology may directly lower the number of accidents. This technology will lower insurance costs and payouts as it minimizes risk and increases the safety of passengers. The goal of this project is to add the proposed technology to the current Advanced Driver Assistance Systems (ADAS) functionality; i.e., include the new abilities alongside other automotive applications such as blind spot monitoring, lane-keep assistance, and forward collision warnings. In addition, this technology may help to advance the commercialization of self-driving vehicles. Due to the flexibility of implementation, it is expected that there may be a significant impact on the automotive transportation community over the next decade.<br/><br/>This I-Corps project is based on the development of advanced computer vision algorithms that provide more reliable driving information in inclement weather. Using a camera as the proposed sensor input, combined with proprietary computer vision algorithms, it is possible to provide the Advanced Driver Assistance Systems (ADAS) with a drivable region on snow-covered roads. The proposed computer vision software was developed from research conducted on how to improve autonomous vehicle performance in adverse weather conditions. This research supports the development of proprietary image processing, image filtering, and machine learning techniques.<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.
