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DTSTART:20220101T000000
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DTSTART;TZID=UTC:20230428T140000
DTEND;TZID=UTC:20230428T150000
DTSTAMP:20260428T212911
CREATED:20230330T110714Z
LAST-MODIFIED:20230330T111735Z
UID:6303-1682690400-1682694000@www.tecosa.center.kth.se
SUMMARY:TECoSA Research Seminar: Collaborative Collision Avoidance of Connected Vehicles Using ADMM with PI-Regulated Lagrangian Multipliers
DESCRIPTION:Speaker:  Kaige Tan\, TECoSA PhD student\nLocation:  Gladan\, Brinellvägen 85 (KTH Campus)\nZoom link: circulated to members (contact Vicki for more info)\nRegister for IRL participation: email vickid@kth.se  by kl.15 on Monday 24 April \n\nABSTRACT: The decentralized approach is popular for the collaborative collision avoidance of connected vehicles in many scenarios. By modeling the task as a collaborative optimal control problem\, Lagrangian methods are widely used to decouple the constraints and enable the decentralized solution. However\, potential constraint-violating behavior will lead to oscillations during the Lagrangian update\, resulting in more iterations and lower real-time efficiency. \nExisting methods generally neither address this shortcoming\, nor explore the Lagrangian update mechanism. This study takes a control perspective\, and solves this collaborative optimal control problem based on an extension of the Alternating Directions Method of Multipliers (ADMM) algorithm by performing the iteration update with a Proportional-Integral- (PI-) regulated controller. The link between the Lagrangian optimization and the PI controller improves the convergence performance during iterations. Simulation results in traffic intersection scenarios demonstrate the advantage of the proposed approach. The preliminary results and future work on its real-time implementation on the 5G testbed will also be discussed.
URL:https://www.tecosa.center.kth.se/event/tecosa-research-seminar-collaborative-collision-avoidance-of-connected-vehicles-using-admm-with-pi-regulated-lagrangian-multipliers/
CATEGORIES:Talks,webinar
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