2304554
Project Grant
Overview
Grant Description
Sbir Phase I: Single-Pulse Radio Frequency Software Suite to Improve Advanced Driver Assistance Systems Safety -The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is focused on developing software to enhance the performance of existing radar hardware on Advanced Driver Assistance Systems (ADAS).
Despite development of ADAS sensing technologies, there are, on average, 14,386 car accidents per day in the United States alone. The performance of these technologies still needs to be improved significantly to ensure the safety of drivers. This project will transform the performance of current ADAS systems, reducing the number of car crashes and fatalities that occur daily.
The total addressable market size for ADAS radar is estimated to be $6.61 billion, and this is the fastest growing market among all ADAS sensors. The current radar technology improvements being introduced today are focused on hardware, machine learning, and artificial intelligence. These current technologies are addressing issues that deal with resolution, but they come with the negative effects of slower processing times, higher cost, and less efficiency.
The successful development of the software solutions in this project will disrupt the ADAS industry as this innovation is physics-based and can unlock the true potential of radar performance.
The intellectual merit of this project is focused on developing and deploying a software suite for remote sensing and data transmission using existing hardware. The software suite involves three primary steps: locating objects, identifying objects, and communicating the findings to other vehicles and/or infrastructure in the surrounding environment. The first two steps fall underneath the remote sensing category. The third falls under the communications category. Simulation development will be done for all three steps.
Once robust simulations have been developed, the remote sensing portion of the software suite will be tested on an industry standard radar unit. The anticipated outcome of the test deployment is that the remote sensing piece of the software suite will enable conventional ADAS radars to achieve higher resolution and lower latency. This deployment is the first step in hardware development to create a safer and complete ADAS software suite.
The results will be used to assess the reliability and feasibility of the proposed software suite in a real-world environment. Additionally, the results will be used to evaluate the efficacy of the software suite by benchmarking performance against current ADAS radar performance.
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.
Despite development of ADAS sensing technologies, there are, on average, 14,386 car accidents per day in the United States alone. The performance of these technologies still needs to be improved significantly to ensure the safety of drivers. This project will transform the performance of current ADAS systems, reducing the number of car crashes and fatalities that occur daily.
The total addressable market size for ADAS radar is estimated to be $6.61 billion, and this is the fastest growing market among all ADAS sensors. The current radar technology improvements being introduced today are focused on hardware, machine learning, and artificial intelligence. These current technologies are addressing issues that deal with resolution, but they come with the negative effects of slower processing times, higher cost, and less efficiency.
The successful development of the software solutions in this project will disrupt the ADAS industry as this innovation is physics-based and can unlock the true potential of radar performance.
The intellectual merit of this project is focused on developing and deploying a software suite for remote sensing and data transmission using existing hardware. The software suite involves three primary steps: locating objects, identifying objects, and communicating the findings to other vehicles and/or infrastructure in the surrounding environment. The first two steps fall underneath the remote sensing category. The third falls under the communications category. Simulation development will be done for all three steps.
Once robust simulations have been developed, the remote sensing portion of the software suite will be tested on an industry standard radar unit. The anticipated outcome of the test deployment is that the remote sensing piece of the software suite will enable conventional ADAS radars to achieve higher resolution and lower latency. This deployment is the first step in hardware development to create a safer and complete ADAS software suite.
The results will be used to assess the reliability and feasibility of the proposed software suite in a real-world environment. Additionally, the results will be used to evaluate the efficacy of the software suite by benchmarking performance against current ADAS radar performance.
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.
Awardee
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Atlanta,
Georgia
30308-1019
United States
Geographic Scope
Single Zip Code
Related Opportunity
None
Solopulse was awarded
Project Grant 2304554
worth $274,059
from National Science Foundation in July 2023 with work to be completed primarily in Atlanta Georgia United States.
The grant
has a duration of 7 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I:Single-Pulse Radio Frequency Software Suite to Improve Advanced Driver Assistance Systems Safety
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is focused on developing software to enhance the performance of existing radar hardware on Advanced Driver Assistance Systems (ADAS). Despite development of ADAS sensing technologies, there are, on average, 14,386 car accidents per day in the United States alone. The performance of these technologies still needs to be improved significantly to ensure the safety of drivers. This project will transform the performance of current ADAS systems, reducing the number of car crashes and fatalities that occur daily. The total addressable market size for ADAS radar is estimated to be $6.61 billion, and this is the fastest growing market among all ADAS sensors. The current radar technology improvements being introduced today are focused on hardware, machine learning, and artificial intelligence. These current technologies are addressing issues that deal with resolution, but they come with the negative effects of slower processing times, higher cost, and less efficiency. The successful development of the software solutions in this project will disrupt the ADAS industry as this innovation is physics-based and can unlock the true potential of radar performance._x000D_ _x000D_ The intellectual merit of this project is focused on developing and deploying a software suite for remote sensing and data transmission using existing hardware. The software suite involves three primary steps: locating objects, identifying objects, and communicating the findings to other vehicles and/or infrastructure in the surrounding environment. The first two steps fall underneath the remote sensing category. The third falls under the communications category. Simulation development will be done for all three steps. Once robust simulations have been developed, the remote sensing portion of the software suite will be tested on an industry standard radar unit. The anticipated outcome of the test deployment is that the remote sensing piece of the software suite will enable conventional ADAS radars to achieve higher resolution and lower latency. This deployment is the first step in hardware development to create a safer and complete ADAS software suite. The results will be used to assess the reliability and feasibility of the proposed software suite in a real-world environment. Additionally, the results will be used to evaluate the efficacy of the software suite by benchmarking performance against current ADAS radar performance._x000D_ _x000D_ 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.
Topic Code
W
Solicitation Number
NSF 22-551
Status
(Complete)
Last Modified 6/21/23
Period of Performance
7/1/23
Start Date
2/29/24
End Date
Funding Split
$274.1K
Federal Obligation
$0.0
Non-Federal Obligation
$274.1K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2304554
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
HHPMRHMGNGX1
Awardee CAGE
9KDG3
Performance District
05
Senators
Jon Ossoff
Raphael Warnock
Raphael Warnock
Representative
Nikema Williams
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $274,059 | 100% |
Modified: 6/21/23