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Summary & Details

An Automatic Emergency Braking System for Collision Avoidance Assist of Multi-Trailer Vehicle Based on Model Prediction Control

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Paper/Info type: SAE Paper

No.2021-01-0117

Pages: 1-16(Total 16 p)

Date of publication: Apr 2021

Publisher: SAE International

Language: English

Event: SAE WCX Digital Summit 2021

Detailed Information

Author(E)	1) Yucheng Liu, 2) John Ball, 3) Sherif Abdelwahed, 4) Ge He
Affiliation(E)	1) Mississippi State University, 2) Mississippi State University, 3) Mississippi State University, 4) Mississippi State University
Abstract(E)	The autonomous collision avoidance problem for multi-trailer vehicle maneuvering is investigated in this paper. Different from conventional vehicle systems that contain one single moving part or multi-parts that can be considered as one rigid body, the interconnection between the tractor and each trailer, and interactions between trailers in the multi-trailer system introduce a high dimensional and highly complex dynamic system for the controller design. The external disturbance and parametric uncertainties further increase the difficulty in system identification and state space formulation. To implement a real time control system for various scenarios where the locations and states of the obstacles are not known beforehand, a supervisory algorithm is designed to convert the control problem to a discrete event system. The model predictive control (MPC) using limited lookahead policy is employed in the proposed algorithm. By viewing the system model under consideration as a finite automaton with a finite number of legal behaviors, the MPC algorithm calculates the complete control outcomes for the entire set of possible control inputs over a limited time horizon. With a proper performance index defined, the designed controller predicts and evaluates the performance of the system such that an optimal control action is selected for the current system states. This process repeats until a predefined objective is reached. Computer based simulation results and Hardware-In-the-Loop (HIL) experiments demonstrate the effectiveness and robustness of the control algorithm as a real time controller.

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