Safe Path Planning in the Presence of Large Communication Delays Using Tube Model Predictive Control

2010 ◽  
Author(s):  
Hojjat Izadi ◽  
Brandon Gordon ◽  
Yomin Zhang
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Tube Model ◽  
Communication Delays ◽  
Safe Path

Tube model predictive control for an autonomous race car

2021 ◽  
pp. 1-23
Author(s):  
A. Wischnewski ◽  
M. Euler ◽  
S. Gümüs ◽  
B. Lohmann
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Tube Model ◽  
Race Car

scholarly journals Striped Parameterized Tube Model Predictive Control

2014 ◽  
Vol 47 (3) ◽  
pp. 11998-12003 ◽  
Author(s):  
Diego Muñoz-Carpintero ◽  
Basil Kouvaritakis ◽  
Mark Cannon
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Tube Model

A method for avoiding obstacles of a self-driving carin the dynamic environment based on model predictive control

2021 ◽  
Author(s):  
N.P. Demenkov ◽  
Kai Zou
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Urban Environment ◽  
Predictive Control ◽  
Potential Field ◽  
Dynamic Environment ◽  
Field Method ◽  
Artificial Potential Field ◽  
Physical Constraints ◽  
Local Path

The paper discusses the problem of obstacle avoidance of a self-driving car in urban road conditions. The artificial potential field method is used to simulate traffic lanes and cars in a road environment. The characteristics of the urban environment, as well as the features and disadvantages of existing methods based on the structure of planning-tracking, are analyzed. A method of local path planning is developed, based on the idea of an artificial potential field and model predictive control in order to unify the process of path planning and tracking to effectively cope with the dynamic urban environment. The potential field functions are introduced into the path planning task as constraints. Based on model predictive control, a path planning controller is developed, combined with the physical constraints of the vehicle, to avoid obstacles and execute the expected commands from the top level as the target for the task. A joint simulation was performed using MATLAB and CarSim programs to test the feasibility of the proposed path planning method. The results show the effectiveness of the proposed method.

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