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Cyber-Physical Systems Virtual Organization
Read-only archive of site from September 29, 2023.
CPS-VO
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Projects
CPS: GOALI: Synergy: Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyberphysical Systems
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Submitted by Ilya V. Kolmanovsky on Fri, 09/23/2016 - 2:22pm
Project Details
Lead PI:
Ilya V. Kolmanovsky
Co-PI(s):
Ella Atkins
Barzan Mozafari
Mark Oliver
Performance Period:
10/01/15
-
09/30/19
Institution(s):
University of Michigan Ann Arbor
Sponsor(s):
National Science Foundation
Award Number:
1544844
1134 Reads. Placed 318 out of 804 NSF CPS Projects based on total reads on all related artifacts.
Abstract:
This project addresses urgent challenges in high confidence validation and verification of automotive vehicles due to on-going and anticipated introduction of advanced, connected and autonomous vehicles into mass production. Since such vehicles operate across both physical and cyber domains, faults can occur in traditional physical components, in cyber components (i.e., algorithms, processors, networks, etc.), or in both. Thus, advanced vehicles need to be tested for both physical and cyber-related fault conditions. The goal of this project is to develop theory, methods, and novel tools for generating and optimizing test trajectories and data inputs that can uncover both physical and cyber faults of future automotive vehicles. The level of vehicle reliability and safety achieved for current vehicles is remarkable considering their mass production, low cost, and wide range of operating conditions. If successful, the research advances made in this project will enable achieving similar levels of reliability and safety for future vehicles relying on advanced driver assistance technologies, connectivity and autonomy. The project will advance the field of cyber-physical systems, in general, and their lifecycle management, in particular. The validation and verification theory and methodology for cyberphysical systems will be expanded for uncovering anomalies and faults, especially using comprehensive case-based and optimization-based techniques for test scenario generation. The theoretical advances and case studies will contribute to the state-of-the-art in optimal control theory, game theory, information theory, data collection and processing, autonomous and connected vehicles, and automotive control. Sampling-based vehicle data acquisition and vehicle-aware data management strategies will be developed which can be applied more broadly, e.g., to cloud-based vehicle prognostics / conditional maintenance and mobile health-monitoring devices. Finally, approaches for efficient on-board data collection and aggregation will be implemented in a Cyber-physical system (CPS) Black Box prototype. The development of a vehicle-aware data management system (VDMS) will be pursued, leading to optimized use of data mining and compression inside the CPS Black Box to aggressively reduce the communication and computational costs. Synergistically with theoretical and methodological advances, automotive case studies will be undertaken with both realistic simulations and real experiments in collaboration with an industrial partner (AVL).
Related Artifacts
Presentations
CPS:GOALI:Synergy: Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyberphysical Systems
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Posters
Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyber-physical Systems
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Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyber-Physical Systems
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CPS: GOALI: Synergy: Maneuver and Data Optimization for High Confidence Testing of Future Automotive CPS
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Publications
A finite state machine based automated driving controller and its stochastic optimization
Co-state initialization for the minimum-time low-thrust trajectory optimization
Low-thrust trajectory optimization for multi-asteroid mission: an indirect approach
Shaping velocity coordinates for generating low-thrust trajectories
Visualization-aware sampling for very large databases
Database learning: Toward a database that becomes smarter every time
A Reference Governor for Nonlinear Systems Based on Quadratic Programming
SnappyData: A Unified Cluster for Streaming, Transactions and Interactice Analytics
Approximate query engines: Commercial challenges and research opportunities
Game theory based traffic modeling for calibration of automated driving algorithms
Game Theoretic Modeling of Driver and Vehicle Interactions for Verification and Validation of Autonomous Vehicle Control Systems
Model-free optimal control based automotive control system falsification
An explicit decision tree approach for automated driving
Iterative model and trajectory refinement for orbital trajectory optimization
A top-down approach to achieving performance predictability in database systems
Hierarchical reasoning game theory based approach for evaluation and testing of autonomous vehicle control systems
Neighboring extremal optimal control for mechanical systems on riemannian manifolds
Videos
Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyber-physical Systems
CPS: GOALI: Synergy: Maneuver and Data Optimization for High Confidence Testing of Future Automotive Cyberphysical Systems
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CPS Domains
Automotive
Testing
Control
Transportation
Validation and Verification
Foundations