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

Format:

Book

Conference/Event

Author/Creator:

Liu, Yucheng, author.

Contributor:

Abdelwahed, Sherif

Ball, John

He, Ge

Conference Name:

SAE WCX Digital Summit (2021-04-13 : Live Online, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

2021-01-0117

Access Restriction:

Restricted for use by site license