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Autonomous Platooning of General Connected Vehicles Using Bayesian Receding Horizon Control

Authors:
Gilchrist Johnson
Tomonari Furukawa
B. Brian Park

Keywords: autonomous following, connected vehicles, recursive Bayesian estimation, receding horizon control.

Abstract:
This paper focuses on futuristic connected vehicles and presents a strategy for autonomous platooning of general connected vehicles including low-speed utility vehicles, which drive over various terrains, not limited to roads. In such general environments, the goal of a following vehicle is to keep following its preceding vehicle with minimum distance and without collision. Since the vehicles are connected, the following vehicle in the proposed strategy receives the controls of its immediate preceding vehicle through communications and predicts a future pose of the preceding vehicle in a receding horizon. Further, the prediction incorporates the inertial motion and is probabilistically executed in the framework of Recursive Bayesian Estimation by fusing the two distributions predicted by a particle filter through Gaussian approximation. The performance of the proposed strategy was investigated using simulated golf carts with a drive-by-wire system. The proposed strategy has been found to improve the accuracy of the conventional following by 30.4%.

Pages: 21 to 26

Copyright: Copyright (c) IARIA, 2024

Publication date: March 10, 2024

Published in: conference

ISSN: 2327-2058

ISBN: 978-1-68558-134-3

Location: Athens, Greece

Dates: from March 10, 2024 to March 14, 2024