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pro vyhledávání: '"John M. Maroli"'
Autor:
John M. Maroli
Publikováno v:
Reliability Engineering & System Safety. 235:109198
Publikováno v:
AIAA Propulsion and Energy 2021 Forum.
Publikováno v:
IFAC-PapersOnLine. 52:186-191
Identification of nonlinear systems is presented using a neural network variant known as the temporal convolutional network (TCN). The identification capabilities of TCNs and standard feedforward neural networks (FNNs) are benchmarked and compared us
Autor:
Ralph Jansen, John M. Maroli, Peter Kascak, Susanah R. Kowalewski, Wesley Miller, David Avanesian, Michael J. Garrett, Matthew G. Granger
Publikováno v:
AIAA Propulsion and Energy 2019 Forum.
A light weight, high efficiency, 11 kW motor controller, which includes the controlling processor and a three phase power inverter, has been developed at NASA Glenn Research Center for NASA's experimental all-electric manned aircraft, X-57, DEP high
Autor:
Lisa Fiorentini, Yasser Bin Salamah, Umit Ozguner, Mohammad Hejase, John M. Maroli, Junbo Jing
Publikováno v:
ACC
Tractor-trailer path tracking in backward motion is a challenging nonlinear control problem in automated vehicle development. The control challenges arise from the fact that a backward driving articulated vehicle is an underactuated system with unsta
Autor:
Yasser Bin Salamah, Lisa Fiorentini, Mohammad Hejase, Umit Ozguner, Junbo Jing, John M. Maroli
Publikováno v:
ITSC
Jackknifing during tractor-trailer reverse driving presents a major challenge in control system design. In this paper, maneuverability conditions were explicitly derived for tractor-trailer systems that are hitched off-axle. A control safety governor
Autor:
Dongfang Yang, Linhui Li, Keith Redmill, Menna El-Shaer, John M. Maroli, Umit Ozguner, Bander A. Jabr, Füsun Özgüner
Publikováno v:
2018 IEEE International Science of Smart City Operations and Platforms Engineering in Partnership with Global City Teams Challenge (SCOPE-GCTC).
In the shared space scenario where pedestrian crowds and autonomous vehicles coexist, the transportation efficiency of the shared space can be improved by predicting the intention of the crowd and adjusting the driving strategy of the autonomous vehi
Publikováno v:
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).
Publikováno v:
Intelligent Vehicles Symposium
In this paper, we analyze mixed traffic environments consisting of fully autonomous vehicles, vehicles capable of communication only, and manually driven vehicles to determine what self-generated content should be shared among peer vehicles for incre