| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | August 12, 2020 |
| Latest Amendment Date: | August 12, 2020 |
| Award Number: | 2007386 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Todd Leen
tleen@nsf.gov (703)292-7215 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2020 |
| End Date: | October 31, 2022 (Estimated) |
| Total Intended Award Amount: | $500,000.00 |
| Total Awarded Amount to Date: | $500,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
4111 MONARCH WAY STE 204 NORFOLK VA US 23508-2561 (757)683-4293 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
5115 Hampton Blvd Norfolk VA US 23529-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | HCC-Human-Centered Computing |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Autonomous vehicles (AVs) are promising to increase transportation safety and security, but the state-of-the-art artificial intelligence (AI) technologies used in AVs are still not sufficient, as evident in fatal crashes involving AVs. In the foreseeable future, human inputs and interventions will still be necessary, at least as a monitor or supervisor in AVs. Monitoring to correctly detect rare but potentially deadly events in AVs requires high levels of vigilance. The required vigilance taxes human supervisors in AVs. This project aims to overcome these challenges through novel collaboration between the AI system and the human driver. This project will result in algorithms and design principles that help reduce road accidents and are broadly applicable to other related intelligent systems in critical areas such as cybersecurity, national defense, and healthcare. Moreover, this project will support multi-disciplinary training of graduate and undergraduate students across disciplines, the development of course modules that provide students interdisciplinary experience critical to shaping the regional and national workforce, and involvement of underrepresented students in STEM fields at the graduate, undergraduate, and pre-K through 12 levels.
This project addresses safety-critical challenges by developing a cognizant human-in-the-loop secure AI mechanism. The project focuses on autonomous driving incorporating three thrusts: (1) Investigate how to maintain human drivers' vigilance through secondary task assignments that incorporate the level of uncertainty in the AI decisions, (2) Develop a fault-tolerant, adversary-aware AI engine that outputs uncertainty levels in its decision as a basis for requesting human inputs. (3) Develop a vigilance-based adaptive task-allocation scheme to calibrate human vigilance online based on a quantitative vigilance model constructed from human-subject data.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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