Award Abstract # 1836952
CPS: Frontier: Collaborative Research: Cognitive Autonomy for Human CPS: Turning Novices into Experts

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: PURDUE UNIVERSITY
Initial Amendment Date: September 16, 2019
Latest Amendment Date: June 29, 2023
Award Number: 1836952
Award Instrument: Continuing Grant
Program Manager: Sylvia Spengler
sspengle@nsf.gov
 (703)292-7347
CNS
 Division Of Computer and Network Systems
CSE
 Direct For Computer & Info Scie & Enginr
Start Date: October 1, 2019
End Date: September 30, 2025 (Estimated)
Total Intended Award Amount: $2,246,039.00
Total Awarded Amount to Date: $2,246,039.00
Funds Obligated to Date: FY 2019 = $895,372.00
FY 2021 = $876,124.00

FY 2022 = $252,764.00

FY 2023 = $221,779.00
History of Investigator:
  • Inseok Hwang (Principal Investigator)
    ihwang@purdue.edu
  • Tahira Reid Smith (Co-Principal Investigator)
  • Neera Jain (Co-Principal Investigator)
  • Brandon Pitts (Co-Principal Investigator)
Recipient Sponsored Research Office: Purdue University
2550 NORTHWESTERN AVE # 1100
WEST LAFAYETTE
IN  US  47906-1332
(765)494-1055
Sponsor Congressional District: 04
Primary Place of Performance: Purdue University
IN  US  47907-2114
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): YRXVL4JYCEF5
Parent UEI: YRXVL4JYCEF5
NSF Program(s): CPS-Cyber-Physical Systems
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01001920DB NSF RESEARCH & RELATED ACTIVIT

01002324DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7918, 8236
Program Element Code(s): 791800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Human interaction with autonomous cyber-physical systems is becoming ubiquitous in consumer products, transportation systems, manufacturing, and many other domains. This project seeks constructive methods to answer the question: How can we design cyber-physical systems to be responsive and personalized, yet also provide high-confidence assurances of reliability? Cyber-physical systems that adapt to the human, and account for the human's ongoing adaptation to the system, could have enormous impact in everyday life as well as in specialized domains (biomedical devices and systems, transportation systems, manufacturing, military applications), by significantly reducing training time, increasing the breadth of the human's experiences with the system prior to operation in a safety-critical environment, improving safety, and improving both human and system performance. Architectures that support dynamic interactions, enabled by advances in computation, communication, and control, can leverage strengths of the human and the automation to achieve new levels of performance and safety.

This research investigates a human-centric architecture for "cognitive autonomy" that couples human psychophysiological and behavioral measures with objective measures of performance. The architecture has four elements: 1) a computable cognitive model which is amenable to control, yet highly customizable, responsive to the human, and context dependent; 2) a predictive monitor, which provides a priori probabilistic verification as well as real-time short-term predictions to anticipate problematic behaviors and trigger the appropriate action; 3) cognitive control, which collaboratively assures both desired safety properties and human performance metrics; and 4) transparent communication, which helps maintain trust and situational awareness through explanatory reasoning. The education and outreach plan focuses on broadening participation of underrepresented minorities through a culturally responsive undergraduate summer research program, which will also provide insights about learning environments that support participation and retention. All research and educational material generated by the project are being made available to the public through the project webpage.

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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(Showing: 1 - 10 of 15)
Luster, Maya S. and Pitts, Brandon J. "Open-Loop Naturalistic Driving: An Assessment of Human Behavior, Performance, and Physiology to Support the Development of Shared Control Strategies" Proceedings of the Human Factors and Ergonomics Society Annual Meeting , 2022 Citation Details
Luster, Maya S. and Pitts, Brandon J. "A Preliminary Investigation into Learning Behaviors in Complex Environments for Human-in-the-Loop Cyber-Physical Systems" Proceedings of the Human Factors and Ergonomics Society Annual Meeting , v.65 , 2021 https://doi.org/10.1177/1071181321651222 Citation Details
Ortiz, Kendric R. and Thorpe, Adam J. and Perez, AnaMaria and Luster, Maya and Pitts, Brandon J. and Oishi, Meeko "Characterizing Within-Driver Variability in Driving Dynamics During Obstacle Avoidance Maneuvers" IFAC-PapersOnLine , v.55 , 2022 https://doi.org/10.1016/j.ifacol.2023.01.096 Citation Details
Sun, Dawei and Hwang, Inseok "On controlled mode discernibility for nonlinear hybrid systems with unknown exogenous input" Automatica , v.142 , 2022 https://doi.org/10.1016/j.automatica.2022.110339 Citation Details
Byeon, Sooyung and Sun, Dawei and Hwang, Inseok "Skill-level-based Hybrid Shared Control for Human-Automation Systems" IEEE International Conference on Systems, Man, and Cybernetics , 2021 https://doi.org/10.1109/SMC52423.2021.9658994 Citation Details
Byeon, Sooyung and Jin, Wanxin and Sun, Dawei and Hwang, Inseok "Human-Automation Interaction for Assisting Novices to Emulate Experts by Inferring Task Objective Functions" AIAA/IEEE Digital Avionics Systems Conference (DASC) , 2021 https://doi.org/10.1109/DASC52595.2021.9594324 Citation Details
Thapliyal, Omanshu and Hwang, Inseok "Approximating Reachable Sets for Neural Network-Based Models in Real Time via Optimal Control" IEEE Transactions on Control Systems Technology , 2023 https://doi.org/10.1109/TCST.2023.3234248 Citation Details
Byeon, Sooyung and Sun, Dawei and Hwang, Inseok "An Inverse Optimal Control Approach for Learning and Reproducing Under Uncertainties" IEEE Control Systems Letters , v.7 , 2023 https://doi.org/10.1109/LCSYS.2022.3226882 Citation Details
Choi, Joonwon and Byeon, Sooyung and Hwang, Inseok "State Prediction of Human-in-the-Loop Multi-rotor System with Stochastic Human Behavior Model" IFAC-PapersOnLine , v.55 , 2022 https://doi.org/10.1016/j.ifacol.2023.01.113 Citation Details
Yuh, Madeleine S. and Byeon, Sooyung and Hwang, Inseok and Jain, Neera "A Heuristic Strategy for Cognitive State-based Feedback Control to Accelerate Human Learning" IFAC-PapersOnLine , v.55 , 2022 https://doi.org/10.1016/j.ifacol.2023.01.111 Citation Details
Clarke, Shanelle G. and Byeon, Sooyung and Hwang, Inseok "A Low Complexity Approach to Model-Free Stochastic Inverse Linear Quadratic Control" IEEE Access , v.10 , 2022 https://doi.org/10.1109/ACCESS.2022.3144933 Citation Details
(Showing: 1 - 10 of 15)

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