Regular Papers

International Journal of Control, Automation and Systems 2019; 17(11): 2850-2861

Published online July 26, 2019

https://doi.org/10.1007/s12555-019-9091-y

© The International Journal of Control, Automation, and Systems

Obstacle Avoidance Path Planning based on Output Constrained Model Predictive Control

Ji-Chang Kim, Dong-Sung Pae, and Myo-Taeg Lim*

Korea University

Abstract

Image processing and control technologies have been widely studied and autonomous vehicles have become an active research area. For autonomous driving, it is essential to generate a safe obstacle avoidance path considering the surrounding environment. This paper devised an algorithm based on a real-time output constrained model predictive control for obstacle avoidance path planning in high speed driving situations. The proposed algorithm was compared with the normal model predictive control algorithm by simulation, including operation times to verify robustness for high speed driving situations. We used the ISO 2631-1 comfort level standard to quantify driver comfort fo r both cases.

Keywords Comfort level, model predictive control, obstacle avoidance, path planning, vehicle dynamics.

Article

Regular Papers

International Journal of Control, Automation and Systems 2019; 17(11): 2850-2861

Published online November 1, 2019 https://doi.org/10.1007/s12555-019-9091-y

Copyright © The International Journal of Control, Automation, and Systems.

Obstacle Avoidance Path Planning based on Output Constrained Model Predictive Control

Ji-Chang Kim, Dong-Sung Pae, and Myo-Taeg Lim*

Korea University

Abstract

Image processing and control technologies have been widely studied and autonomous vehicles have become an active research area. For autonomous driving, it is essential to generate a safe obstacle avoidance path considering the surrounding environment. This paper devised an algorithm based on a real-time output constrained model predictive control for obstacle avoidance path planning in high speed driving situations. The proposed algorithm was compared with the normal model predictive control algorithm by simulation, including operation times to verify robustness for high speed driving situations. We used the ISO 2631-1 comfort level standard to quantify driver comfort fo r both cases.

Keywords: Comfort level, model predictive control, obstacle avoidance, path planning, vehicle dynamics.

IJCAS
December 2024

Vol. 22, No. 12, pp. 3545~3811

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