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A Nonlinear Model Predictive Control Design for Autonomous Multivehicle Merging into Platoons
Journal Article
09-10-01-0004
ISSN: 2327-5626, e-ISSN: 2327-5634
Sector:
Topic:
Citation:
Goli, M. and Eskandarian, A., "A Nonlinear Model Predictive Control Design for Autonomous Multivehicle Merging into Platoons," SAE Int. J. Trans. Safety 10(1):73-91, 2022, https://doi.org/10.4271/09-10-01-0004.
Language:
English
Abstract:
Integrated control for automated vehicles in platoons with nonlinear coupled
dynamics is developed in this article. A nonlinear MPC approach is used to
address the multi-input multi-output (MIMO) nature of the problem, the nonlinear
vehicle dynamics, and the platoon constraints. The control actions are
determined by using model-based prediction in conjunction with constrained
optimization. Two distinct scenarios are then simulated. The first scenario
consists of the multivehicle merging into an existing platoon in a controlled
environment in the absence of noise, whereas the effects of external
disturbances, modeling errors, and measurement noise are simulated in the second
scenario. An extended Kalman filter (EKF) is utilized to estimate the system
states under the sensor and process noise effectively. The simulation results
show that the proposed approach is a suitable tool to handle the nonlinearities
in the vehicle dynamics, the complication of the multivehicle merging scenario,
and the presence of modeling uncertainties and measurement noise.